Literatura académica sobre el tema "Heuristiek"
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Artículos de revistas sobre el tema "Heuristiek"
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Burgers, Jan y Rik Hoekstra. "De Digitale Charterbank Nederland". BMGN - Low Countries Historical Review 136, n.º 3 (30 de septiembre de 2021): 92–119. http://dx.doi.org/10.51769/bmgn-lchr.6997.
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In de Nederlandse archieven worden tienduizenden oorkonden (ofwel charters) bewaard uit de middeleeuwen en de vroegmoderne tijd. Dit materiaal vormt een onschatbare bron van informatie over allerlei maatschappelijke aspecten. Toch worden deze oorkonden in het historisch onderzoek nog weinig gebruikt, vanwege de gecompliceerde heuristiek: de documenten zijn verspreid over tientallen archieven en honderden archieffondsen. De Digitale Charterbank Nederland (DCN) maakt het grootste deel van dit corpus nu toegankelijk in een geïntegreerde database, waarin alle stukken vindbaar zijn. Ons artikel bespreekt de opzet van DCN en de praktische consequenties daarvan voor de gebruiker. De database kent specifieke mogelijkheden maar ook bepaalde beperkingen, en dit artikel toont hoe DCN kan helpen bij zowel gedetailleerd onderzoek naar personen of plaatsen als bij brede studies over een lange periode. Tevens wordt ingegaan op de invloed van de nieuwe grootschalige digitale bronontsluitingen en de bijbehorende hulpmiddelen en technieken op het historisch onderzoek.The Dutch archives hold tens of thousands of charters from the Middle Ages and early modern period, providing an invaluable source of information on various societal aspects. Yet, this material is scarcely used in historical research mainly due to its complicated heuristics: the documents are spread across dozens of archives and hundreds of archival funds. The Digitale Charterbank Nederland (DCN) now makes most of this corpus accessible through an integrated database in which all documents can be found. Our article discusses the set-up of DCN and its practical consequences for the user. The database has specific possibilities but also certain limitations, and this article shows how DCN can help with both detailed research into persons or places, and with more broadly oriented research covering a long period of time. The article further includes a reflection on the impact of new large scale digital source retrieval systems and the associated tools and techniques on historical research.
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Lazuarni, Shafiera, William Wendy Ary, Try Wulandari y Emilda Emilda. "Apakah Investor Milenial Penyebab Terbentuknya Teknikal Anomali di Pasar Modal Indonesia?" MBIA 21, n.º 2 (28 de agosto de 2022): 125–39. http://dx.doi.org/10.33557/mbia.v21i2.1747.
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This study aims to examine the role of millennial investors' simplification behavior (heuristic) on the formation of technical anomalies in the capital market and the role of these anomalies on investment performance. The method of the data analysis used the SEM (Structural Equation Modeling) method with the WarpPLS analysis tool. The Variance Accounted For (VAF) method was added in this study as an additional test to explore whether technical anomalies can mediate the effect of heuristics on investment performance. The results proved that the heuristic behavior (availability, representativeness, and hindsight) of millennial investors is one of the factors causing technical anomalies in the capital market, except for the availability heuristic. The limitations of this study were the first measurement items/items used were minimal, amounting to two to four items for each construct. Second, this study could not detail how millennial investors behaved when selling or buying shares. This study is essential as investors can understand their investment behavior and they can make better decisions. Further, providing information regarding the behavior of millennial investors to the government because the millennial generation is an essential key in encouraging them to be at the forefront of the Indonesian economy. The implication is that the government can develop strategies and policies to increase the involvement of the millennial generation in investing in the capital market.
Keywords: Investor Behavior, Millennial Investors, Anomalies, Heuristics, Capital Market
Abstrak
Penelitian ini bertujuan menguji peran perilaku penyederhanaan (heuristik) investor milenial terhadap terbentuknya teknikal anomali di pasar modal dan peran anomali tersebut terhadap kinerja investasi. Metode analisis data menggunakan metode SEM (Structural Equation Modeling) dengan alat analisis WarpPLS. Metode Variance Accounted For (VAF) juga ditambahkan dalam penelitian ini sebagai ujian tambahan untuk mengeksplorasi apakah teknikal anomali mampu memediasi pengaruh antara heuristik terhadap kinerja investasi. Hasil penelitian menunjukkan bahwa perilaku heuristik (availability, representativeness, dan hindsight) investor milenial terbukti menjadi salah satu faktor penyebab terjadinya teknikal anomali di pasar modal, kecuali availability heuristik. Keterbatasan penelitian ini pertama item pengukuran/item yang digunakan sangat terbatas berjumlah dua hingga empat item untuk masing-masing konstruk. Kedua, penelitian ini tidak mampu menangkap secara detail bagaimana perilaku investor milenial secara terpisah saat menjual atau membeli saham. Penelitian ini penting dilakukan agar investor dapat memahami perilaku investasi mereka sehingga mampu mengambil keputusan lebih baik. Kedua, memberikan informasi terkait perilaku investor milenial ke pemerintahan karena generasi milenial menjadi kunci penting dalam mendorong mereka menjadi garda terdepan dalam perekonomian Indonesia. Implikasinya pemerintah dapat menyusun strategi dan kebijakan dalam peningkatan keterlibatan generasi milenial dalam berinvestasi di pasar modal.
Kata Kunci: Perilaku Investor, Investor Milenial, Anomali, Heuristik, Pasar Modal
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Seipp, Jendrik. "Better Orders for Saturated Cost Partitioning in Optimal Classical Planning". Proceedings of the International Symposium on Combinatorial Search 8, n.º 1 (1 de septiembre de 2021): 149–53. http://dx.doi.org/10.1609/socs.v8i1.18438.
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Cost partitioning is a general method for adding multiple heuristic values admissibly. In the setting of optimal classical planning, saturated cost partitioning has recently been shown to be the cost partitioning algorithm of choice for pattern database heuristics found by hill climbing, systematic pattern database heuristics and Cartesian abstraction heuristics. To evaluate the synergy of the three heuristic types, we compute the saturated cost partitioning over the combined sets of heuristics and observe that the resulting heuristic is outperformed by the heuristic that simply maximizes over the three saturated cost partitioning heuristics computed separately for each heuristic type. Our new algorithm for choosing the orders in which saturated cost partitioning considers the heuristics allows us to compute heuristics outperforming not only the maximizing heuristic but even state-of-the-art planners.
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Sihotang, Emil Hasudungan, Muhamad Adam, Marlina Widiyanti y Yuliani Yuliani. "PENGARUH PERILAKU KEUANGAN HEURISTIK TERHADAP KEPUTUSAN INVESTASI SAHAM PADA BURSA EFEK INDONESIA DENGAN INVESTASI ETIS SEBAGAI VARIABEL INTERVENING STUDI EMPIRIS PADA MASYARAKAT INVESTOR KOTA PALEMBANG". Jurnal Riset Ekonomi dan Bisnis 13, n.º 1 (21 de abril de 2020): 28. http://dx.doi.org/10.26623/jreb.v13i1.2108.
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<p class="BasicParagraph">Tujuan dari penelitian ini untuk mengetahui bukti empiris pengaruh perilaku keuangan heuristik (<em>salience, rerpresentativness dan mental accounting</em>) dan investasi etis terhadap keputusan investasi saham yang dilakukan oleh investor individu di kota Palembang pada tahun 2019. Penelitian ini bersifat kausal menggunakan data primer 145 responden dengan teknik purposive sampling. Program analisis Structural Equation Modeling (SEM) Amos digunakan untuk mengukur hubungan antara variabel penelitian. Hasil penelitian menunjukkan bahwa perilaku keuangan heuristik salience dan mental accounting berpengaruh signifikan terhadap keputusan investasi, sedangkan <em>representativness</em> tidak signifikan terhadap keputusan investasi dan investasi etis mampu memediasi perilaku keuangan heuristik terhadap keputusan investasi.</p><p class="BasicParagraph"><strong><em>The purpose of this study is to find out empirical evidence of the influence of financial heuristics (salience, rerpresentativness and mental accounting) and ethical investment on investment decisions made by individual investors in the city of Palembang in 2019. This study uses causal data using primary data of 145 respondents with taking techniques purposive sample. Analysis of the Amos Structural Equation Modeling (SEM) program is used to measure the relationship between research variables. The results showed heuristic financial facts salience and mental accounting have a significant effect on investment decisions, while representation does not have a significant effect on investment returns and ethical investment is able to mediate heuristic financial problems on investment decisions.</em></strong></p>
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Drake, John H., Matthew Hyde, Khaled Ibrahim y Ender Ozcan. "A genetic programming hyper-heuristic for the multidimensional knapsack problem". Kybernetes 43, n.º 9/10 (3 de noviembre de 2014): 1500–1511. http://dx.doi.org/10.1108/k-09-2013-0201.
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Purpose – Hyper-heuristics are a class of high-level search techniques which operate on a search space of heuristics rather than directly on a search space of solutions. The purpose of this paper is to investigate the suitability of using genetic programming as a hyper-heuristic methodology to generate constructive heuristics to solve the multidimensional 0-1 knapsack problem Design/methodology/approach – Early hyper-heuristics focused on selecting and applying a low-level heuristic at each stage of a search. Recent trends in hyper-heuristic research have led to a number of approaches being developed to automatically generate new heuristics from a set of heuristic components. A population of heuristics to rank knapsack items are trained on a subset of test problems and then applied to unseen instances. Findings – The results over a set of standard benchmarks show that genetic programming can be used to generate constructive heuristics which yield human-competitive results. Originality/value – In this work the authors show that genetic programming is suitable as a method to generate reusable constructive heuristics for the multidimensional 0-1 knapsack problem. This is classified as a hyper-heuristic approach as it operates on a search space of heuristics rather than a search space of solutions. To our knowledge, this is the first time in the literature a GP hyper-heuristic has been used to solve the multidimensional 0-1 knapsack problem. The results suggest that using GP to evolve ranking mechanisms merits further future research effort.
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Seipp, Jendrik, Florian Pommerening y Malte Helmert. "New Optimization Functions for Potential Heuristics". Proceedings of the International Conference on Automated Planning and Scheduling 25 (8 de abril de 2015): 193–201. http://dx.doi.org/10.1609/icaps.v25i1.13714.
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Potential heuristics, recently introduced by Pommerening et al., characterize admissible and consistent heuristics for classical planning as a set of declarative constraints. Every feasible solution for these constraints defines an admissible heuristic, and we can obtain heuristics that optimize certain criteria such as informativeness by specifying suitable objective functions. The original paper only considered one such objective function: maximizing the heuristic value of the initial state. In this paper, we explore objectives that attempt to maximize heuristic estimates for all states (reachable and unreachable), maximize heuristic estimates for a sample of reachable states, maximize the number of detected dead ends, or minimize search effort. We also search for multiple heuristics with complementary strengths that can be combined to obtain even better heuristics.
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Ursani, Ziauddin y David W. Corne. "Introducing Complexity Curtailing Techniques for the Tour Construction Heuristics for the Travelling Salesperson Problem". Journal of Optimization 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/4786268.
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In this paper, complexity curtailing techniques are introduced to create faster version of insertion heuristics, that is, cheapest insertion heuristic (CIH) and largest insertion heuristic (LIH), effectively reducing their complexities fromO(n3)toO(n2)with no significant effect on quality of solution. This paper also examines relatively not very known heuristic concept of max difference and shows that it can be culminated into a full-fledged max difference insertion heuristic (MDIH) by defining its missing steps. Further to this the paper extends the complexity curtailing techniques to MDIH to create its faster version. The resultant heuristic, that is, fast max difference insertion heuristic (FMDIH), outperforms the “farthest insertion” heuristic (FIH) across a wide spectrum of popular datasets with statistical significance, even though both the heuristics have the same worst case complexity ofO(n2). It should be noted that FIH is considered best among lowest order complexity heuristics. The complexity curtailing techniques presented here open up the new area of research for their possible extension to other heuristics.
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Narayanan, Venkatraman, Sandip Aine y Maxim Likhachev. "Improved Multi-Heuristic A* for Searching with Uncalibrated Heuristics". Proceedings of the International Symposium on Combinatorial Search 6, n.º 1 (1 de septiembre de 2021): 78–86. http://dx.doi.org/10.1609/socs.v6i1.18350.
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Recently, several researchers have brought forth the benefits of searching with multiple (and possibly inadmissible) heuristics, arguing how different heuristics could be independently useful in different parts of the state space. However, algorithms that use inadmissible heuristics in the traditional best-first sense, such as the recently developed Multi-Heuristic A* (MHA*), are subject to a crippling calibration problem: they prioritize nodes for expansion by additively combining the cost-to-come and the inadmissible heuristics even if those heuristics have no connection with the cost-to-go (e.g., the heuristics are uncalibrated) . For instance, if the inadmissible heuristic were an order of magnitude greater than the perfect heuristic, an algorithm like MHA* would simply reduce to a weighted A* search with one consistent heuristic. In this work, we introduce a general multi-heuristic search framework that solves the calibration problem and as a result a) facilitates the effective use of multiple uncalibrated inadmissible heuristics, and b) provides significantly better performance than MHA* whenever tighter sub-optimality bounds on solution quality are desired. Experimental evaluations on a complex full-body robotics motion planning problem and large sliding tile puzzles demonstrate the benefits of our framework.
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Pommerening, Florian, Gabriele Röger, Malte Helmert y Blai Bonet. "LP-Based Heuristics for Cost-Optimal Planning". Proceedings of the International Conference on Automated Planning and Scheduling 24 (11 de mayo de 2014): 226–34. http://dx.doi.org/10.1609/icaps.v24i1.13621.
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Many heuristics for cost-optimal planning are based on linear programming. We cover several interesting heuristics of this type by a common framework that fixes the objective function of the linear program. Within the framework, constraints from different heuristics can be combined in one heuristic estimate which dominates the maximum of the component heuristics. Different heuristics of the framework can be compared on the basis of their constraints. With this new method of analysis, we show dominance of the recent LP-based state-equation heuristic over optimal cost partitioning on single-variable abstractions. We also show that the previously suggested extension of the state-equation heuristic to exploit safe variables cannot lead to an improved heuristic estimate. We experimentally evaluate the potential of the proposed framework on an extensive suite of benchmark tasks.
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Shanklin, Roslyn, Philip Kortum y Claudia Ziegler Acemyan. "Adaptation of Heuristic Evaluations for the Physical Environment". Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, n.º 1 (diciembre de 2020): 1135–39. http://dx.doi.org/10.1177/1071181320641272.
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Previous work has investigated the need for domain specific heuristics. Nielsen’s ten heuristics offer a general list of principles, but those principles may not capture usability issues specific to a given interface. Studies have demonstrated methods to establish a domain specific heuristic set, but very little research has been conducted on interfaces in the physical environment, creating a gap in the state-of-the-art. The research described in this paper aims to address this gap by developing an environmental heuristic set; the heuristic set was developed specifically for the Houston light rail system, METRORail. Following development, the heuristic set was validated against Nielsen’s more general heuristics through several field studies. Results highlighted that there were significantly more usability issues identified when using the environment-based heuristics than the general heuristics. This suggests that domain specific heuristics provide a framework that allows evaluators to capture usability issues particular to the interface of the physical environment.
Tesis sobre el tema "Heuristiek"
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Buvari, Oscar. "Heuristisk utvärdering : En jämförelse mellan heuristiska uppsättningar för användargränssnitt i spel". Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-13868.
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Det användarcentrerande tillvägagångssättet från människa-datorinteraktion (MDI) har anammats av många andra discipliner – där två aktuella discipliner som gjort detta är User Experience Design (UXD), vars mål är att skapa användbara mjukvaror ifrån användarnas perspektiv, och speldesign, som syftar till att skapa underhållande mjukvaror. För att göra detta använder båda dessa discipliner heuristisk utvärdering; där UXD använder traditionella heuristiker för användbarhet, medan speldesign på akademisk nivå utvecklat nya uppsättningar med spelheuristiker som är anpassade för spel. Dessa nya uppsättningar är inte validerade, då de brister i empiriska studier. Därför syftar detta arbete till att validera två nya uppsättningar spelheuristiker, samt att undersöka vilket extra värde de har, om något, gentemot traditionella uppsättningar heuristiker för användbarhet under utvärdering av gränssnitt i spel. Metoden bestod först av en heuristisk utvärdering där tre utvärderare utvärderade den globala Spelmenyn i RPG-spelet The Witcher 3: Wild Hunt, där båda uppsättningarna spelheuristiker och Nielsens 10 heuristiker för användbarhet användes, och sedan gjordes ett användartest på samma gränssnitt. Användartestet bestod av fem deltagare, alla män mellan åldrarna 20-23 och var studenter vid Högskolan i Skövde. Undersökningen resulterade i tre totala listor problem, en från respektive uppsättning, som sedan jämfördes med en lista med problem från användartestet. Slutsatsen blev att spelheuristikerna är lämpliga att använda under utvärderingen av menyer som liknar Spelmenyn, och är därmed validerade under dessa omständigheter. Dock finns det inget underlag att anta att spelheuristikerna medför ett extra märkbart värde än heuristikerna för användbarhet under utvärderingen av gränssnitt i spel.
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Peake, Katharine Louise. "Composition heuristics and theories and a proposed heuristic for business writing". CSUSB ScholarWorks, 2007. https://scholarworks.lib.csusb.edu/etd-project/3282.
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Menchini, Tom y Karl Åkerlund. "Jämförelse av nya och gamla heuristiker inom heuristisk utvärdering: Är det dags för förändring?" Thesis, Umeå universitet, Institutionen för psykologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-122223.
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Heuristisk utvärdering av användargränssnitt är känt för att vara billigare och snabbare än användarutvärdering. Ett problem är att den inte finner samma användbarhetsproblem som riktiga användare. Petrie och Powers heuristiker för heuristisk utvärdering utvärderades för att utreda ifall de löst detta problem. Syftet för studien var att bidra till forskningsområdet genom att styrka eller motsäga tidigare fynd. Genom en fallstudie utfördes användarutvärdering och heuristisk utvärdering och mått på Validity, Thoroughness och Effectiveness jämfördes mellan tre olika studier. Vid användarutvärdering användes riktiga användare som arbetar med programvaran. Utvärderarna vid heuristisk utvärdering läste kognitionsvetenskap och räknades som noviser inom användbarhetsutvärdering. Petrie och Powers heuristiker presterade likvärdigt med Nielsens heuristiker i de andra studierna som jämfördes mot. Hypotesen att Petrie och Powers heuristiker bättre skulle predicera användbarhetsproblem gick följaktligen inte att styrka.
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Silva, Renato Teixeira da [UNESP]. "Aplicação de meta-heurísticas na resolução do problema de balanceamento e designação de trabalhadores com deficiência em linha de produção". Universidade Estadual Paulista (UNESP), 2012. http://hdl.handle.net/11449/93081.
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silva_rt_me_guara.pdf: 445223 bytes, checksum: f6563e16194940a8f4f8abc7c03ac033 (MD5)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
A Organização Internacional do Trabalho estima que existem cerca de 650 milhões de pessoas com deficiência em idade produtiva. No entanto, esta parcela da população possui altos índices de desemprego devido a várias barreiras. Uma alternativa para facilitar a inclusão dessas pessoas é a criação de Centros de Trabalho para pessoas com Deficiência (CTD`s) onde as pessoas com deficiência tenham a oportunidade de experimentar um ambiente de trabalho real antes de irem para um emprego “normal”. Neste tipo de ambiente, onde é impossível ao gestor prever quais trabalhadores estarão disponíveis a cada dia devido às altas taxas de absenteísmo, há a necessidade de se definir uma organização mais produtiva diariamente. Neste contexto se torna oportuna a utilização do Problema de Balanceamento de Linha e Designação de Trabalhadores (em inglês ALWABP), onde se busca minimizar o tempo de ciclo a partir de um dado número de trabalhadores, alocando tarefas às estações de trabalho e trabalhadores às estações, tendo em vista que alguns trabalhadores podem ser muito lentos para executar certas tarefas ou até incapazes, devido a alguma deficiência que eles apresentam, e muito eficientes na execução de outras. O objetivo geral desta dissertação consiste em empregar diferentes meta-heurísticas para resolver o ALWABP, comparando com os melhores resultados das instâncias encontradas na literatura. Dentre várias meta-heurísticas disponíveis na literatura foram utilizados o Harmony Search (HS), o Adaptive Large Neighborhood Search (ALNS) e o Clustering Search (CS) utilizando o HS e o ALNS como heurísticas geradoras de soluções. Cada uma das quatro implementações foram testadas em 320 instâncias propostas na literatura divididas em quatro famílias. Os experimentos computacionais mostraram bons resultados...
The International Labour Organization estimates that there are approximately 650 million disabled people in working age. However, this population presents high rates of unemployment due to numerous barriers. An alternative to facilitate the inclusion of these people is the establishment of Centers for Working People with Disabilities where people with disabilities have the opportunity to experience a real work environment before going to a “normal” job. In this type of environment, where it is impossible to predict which workers will be available each day due to high rates of absence in this population, there is a need to define a more productive organization on a daily basis. In this context it becomes appropriate to use the Assembly Line Worker Assignment and Balancing Problem (ALWABP), which seeks to minimize the cycle time for a given number of workers, assigning tasks to workstations and workers to stations, considering that some workers may be too slow to perform certain tasks, or even unable due to some deficiency they present, and very efficient in performing others. The aim of this dissertation is to employ different meta-heuristics to solve the ALWABP, comparing with the best results of instances found in the literature. Among several meta-heuristics available in the literature were used Harmony Search (HS), Adaptive Large Neighborhood Search (ALNS) and Clustering Search (CS) using the HS and ALNS as heuristics for the generation of solutions. Each of the four implementations has been tested in 320 instances proposed in the literature, classified into four families. The computational experiments showed good results, and in some instances obtaining better solution values best known. Conclusions regarding... (Complete abstract click electronic access below)
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Silva, Renato Teixeira da. "Aplicação de meta-heurísticas na resolução do problema de balanceamento e designação de trabalhadores com deficiência em linha de produção /". Guaratinguetá : [s.n.], 2012. http://hdl.handle.net/11449/93081.
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Orientador: Galeno José de SenaBanca: Marcos Antonio Pereira
Banca: Anibal Tavares de Azevedo
Resumo: A Organização Internacional do Trabalho estima que existem cerca de 650 milhões de pessoas com deficiência em idade produtiva. No entanto, esta parcela da população possui altos índices de desemprego devido a várias barreiras. Uma alternativa para facilitar a inclusão dessas pessoas é a criação de Centros de Trabalho para pessoas com Deficiência (CTD's) onde as pessoas com deficiência tenham a oportunidade de experimentar um ambiente de trabalho real antes de irem para um emprego "normal". Neste tipo de ambiente, onde é impossível ao gestor prever quais trabalhadores estarão disponíveis a cada dia devido às altas taxas de absenteísmo, há a necessidade de se definir uma organização mais produtiva diariamente. Neste contexto se torna oportuna a utilização do Problema de Balanceamento de Linha e Designação de Trabalhadores (em inglês ALWABP), onde se busca minimizar o tempo de ciclo a partir de um dado número de trabalhadores, alocando tarefas às estações de trabalho e trabalhadores às estações, tendo em vista que alguns trabalhadores podem ser muito lentos para executar certas tarefas ou até incapazes, devido a alguma deficiência que eles apresentam, e muito eficientes na execução de outras. O objetivo geral desta dissertação consiste em empregar diferentes meta-heurísticas para resolver o ALWABP, comparando com os melhores resultados das instâncias encontradas na literatura. Dentre várias meta-heurísticas disponíveis na literatura foram utilizados o Harmony Search (HS), o Adaptive Large Neighborhood Search (ALNS) e o Clustering Search (CS) utilizando o HS e o ALNS como heurísticas geradoras de soluções. Cada uma das quatro implementações foram testadas em 320 instâncias propostas na literatura divididas em quatro famílias. Os experimentos computacionais mostraram bons resultados... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: The International Labour Organization estimates that there are approximately 650 million disabled people in working age. However, this population presents high rates of unemployment due to numerous barriers. An alternative to facilitate the inclusion of these people is the establishment of Centers for Working People with Disabilities where people with disabilities have the opportunity to experience a real work environment before going to a "normal" job. In this type of environment, where it is impossible to predict which workers will be available each day due to high rates of absence in this population, there is a need to define a more productive organization on a daily basis. In this context it becomes appropriate to use the Assembly Line Worker Assignment and Balancing Problem (ALWABP), which seeks to minimize the cycle time for a given number of workers, assigning tasks to workstations and workers to stations, considering that some workers may be too slow to perform certain tasks, or even unable due to some deficiency they present, and very efficient in performing others. The aim of this dissertation is to employ different meta-heuristics to solve the ALWABP, comparing with the best results of instances found in the literature. Among several meta-heuristics available in the literature were used Harmony Search (HS), Adaptive Large Neighborhood Search (ALNS) and Clustering Search (CS) using the HS and ALNS as heuristics for the generation of solutions. Each of the four implementations has been tested in 320 instances proposed in the literature, classified into four families. The computational experiments showed good results, and in some instances obtaining better solution values best known. Conclusions regarding... (Complete abstract click electronic access below)
Mestre
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Méllo, Fábio Gavião Avelino de [UNESP]. "Método heurístico para criação de linhas de trabalho em problemas de escalonamento de pessoal". Universidade Estadual Paulista (UNESP), 2014. http://hdl.handle.net/11449/106401.
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000757731.pdf: 2807037 bytes, checksum: 5aa196a9569db15583f96a6a1fbce2c8 (MD5)A presente pesquisa trata do desenvolvimento de um método de solução do problema de construção de linhas de trabalho para a área de escalonamento de pessoal. Foram investigados diversos artigos da área de programação de pessoal com o objetivo de escolher precisamente o tema da pesquisa. Este tema escolhido foi o da construção de linhas de trabalho para empresas de ônibus interurbanos no Brasil. De posse do tema escolhido, foram analisados os métodos usados para formular e resolver o problema. Como resultado foi decidido o uso de uma formulação de cobertura de conjuntos não unicusto para representar o problema em estudo e o uso de um método heurístico para resolver o mesmo. Esta heurística divide a solução do problema em duas fases. A primeira é a fase construtiva, em que o espaço de solução é montado e linhas de trabalho são investigadas e aquelas viáveis são agrupadas formando um conjunto de linhas viáveis e qualificadas. A segunda é a fase de otimização ou de busca local em que um algoritmo evolutivo, baseado em algoritmo genético, irá procurar a melhor solução dentro desse subconjunto de linhas viáveis e qualificadas obtidas na primeira fase. Estes dois procedimentos se repetem até que um critério de parada seja atingido. Testes computacionais foram realizados no sentido de demonstrar a eficácia e eficiência do método proposto. Em seguida, o problema da programação de dias de expediente e de folga, neste trabalho denominado problema de padrões de folga, é formulado e resolvido. Algumas propostas para integrar a solução do problema de criação de linhas de trabalho à do problema de padrões de folga são apresentadas e discutidas
This thesis deals with the development of a method for solving the problem of construction of lines of work for the application area of personnel scheduling. Several articles were analyzed in order to matching precisely the subject of the research. An in-depth review of the processes used for formulating and solving such a kind of problem in the literature was conducted. As a result, it was decided to formulating the problem as a non unicost set covering problem and to use a heuristic method to solve it. The proposed heuristic is a twofold algorithm. The first is the construction phase, in which the solution space is scanned and working lines are investigated and those feasible are grouped together forming a set of feasible and qualified lines. The second phase is the optimization or local search in which an evolutionary algorithm based on genetic algorithm will search for the best solution within this set of feasible and qualified lines obtained in the first phase. These two phases are repeated until a stop criterion is reached. Computational tests were performed to demonstrate the effectiveness and efficiency of the proposed method. Then, the tour scheduling problem is addressed in the context of finding shifts of work-days and days-off scheduling. Its resolved by deterministic techniques. Some methods are then discussed on how to integrating both of the solutions of the lines of work and the tour scheduling problems
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Méllo, Fábio Gavião Avelino de. "Método heurístico para criação de linhas de trabalho em problemas de escalonamento de pessoal /". Guaratinguetá, 2014. http://hdl.handle.net/11449/106401.
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Orientador: Edson Luiz França SenneBanca: Galeno José de Sena
Banca: José Roberto Dale Luche
Banca: Anibal Tavares de Azevedo
Banca: Kelly Cristina Poldi
Resumo : A presente pesquisa trata do desenvolvimento de um método de solução do problema de construção de linhas de trabalho para a área de escalonamento de pessoal. Foram investigados diversos artigos da área de programação de pessoal com o objetivo de escolher precisamente o tema da pesquisa. Este tema escolhido foi o da construção de linhas de trabalho para empresas de ônibus interurbanos no Brasil. De posse do tema escolhido, foram analisados os métodos usados para formular e resolver o problema. Como resultado foi decidido o uso de uma formulação de cobertura de conjuntos não unicusto para representar o problema em estudo e o uso de um método heurístico para resolver o mesmo. Esta heurística divide a solução do problema em duas fases. A primeira é a fase construtiva, em que o espaço de solução é montado e linhas de trabalho são investigadas e aquelas viáveis são agrupadas formando um conjunto de linhas viáveis e qualificadas. A segunda é a fase de otimização ou de busca local em que um algoritmo evolutivo, baseado em algoritmo genético, irá procurar a melhor solução dentro desse subconjunto de linhas viáveis e qualificadas obtidas na primeira fase. Estes dois procedimentos se repetem até que um critério de parada seja atingido. Testes computacionais foram realizados no sentido de demonstrar a eficácia e eficiência do método proposto. Em seguida, o problema da programação de dias de expediente e de folga, neste trabalho denominado problema de padrões de folga, é formulado e resolvido. Algumas propostas para integrar a solução do problema de criação de linhas de trabalho à do problema de padrões de folga são apresentadas e discutidas
Abstract: This thesis deals with the development of a method for solving the problem of construction of lines of work for the application area of personnel scheduling. Several articles were analyzed in order to matching precisely the subject of the research. An in-depth review of the processes used for formulating and solving such a kind of problem in the literature was conducted. As a result, it was decided to formulating the problem as a non unicost set covering problem and to use a heuristic method to solve it. The proposed heuristic is a twofold algorithm. The first is the construction phase, in which the solution space is scanned and working lines are investigated and those feasible are grouped together forming a set of feasible and qualified lines. The second phase is the optimization or local search in which an evolutionary algorithm based on genetic algorithm will search for the best solution within this set of feasible and qualified lines obtained in the first phase. These two phases are repeated until a stop criterion is reached. Computational tests were performed to demonstrate the effectiveness and efficiency of the proposed method. Then, the tour scheduling problem is addressed in the context of finding shifts of work-days and days-off scheduling. Its resolved by deterministic techniques. Some methods are then discussed on how to integrating both of the solutions of the lines of work and the tour scheduling problems
Doutor
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Aliano, Filho Angelo [UNESP]. "Metaheurísticas em um problema de rotação de culturas". Universidade Estadual Paulista (UNESP), 2012. http://hdl.handle.net/11449/95055.
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alianofilho_a_me_botib.pdf: 803708 bytes, checksum: 7df8e5e731e86aee69b812455f899135 (MD5)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
Um dos focos centrais na produção vegetal, discutidos ultimamente, e a utilização de medidas que visam um planejamento sustentável e ecológico, tendo em vista a degradação ambiental ocorrida nos ultimos anos. Por este motivo, a Rotação de Culturas tem ganhado destaque na literatura, pois e um meio de produção cujos princípios práticos viabilizam uma agricultura ecológica e produtiva. Esta prática, uma vez bem conduzida pelos agricultores rurais, traz inúmeros benefícios, visto que o controle de pragas, patógenos e de plantas daninhas e realizado biologicamente, diminuindo a ação de pesticidas prejudiciais ao meio ambiente e medidas de recuperação do solo, tornando-o sempre fértil. Nesta dissertação, e apresentado um modelo de otimização 0-1 para o problema de Rotação de Culturas, cujo objetivo foi encontrar uma programação de plantio de hortaliças que maximize o lucro da produção, levando-se em consideração restrições de epoca de semeadura para cada cultura considerada, o não cultivo de plantas de mesma família em lotes vizinhos, proibição de plantio consecutivo de plantas de mesma família botânica em um mesmo lote, a necessidade de adubação verde, período de descanso do solo e de demanda. Nesta modelagem, foi considerada uma area de plantio genérica, cujos lotes são irregularmente distribuídos e de diferentes tamanhos. Para resolução do problema, foram desenvolvidas e implementadas a seguintes metaheurísticas: (a) Algoritmo Gen etico, (b) Simulated Annealing, e as abordagens mistas (c) Algoritmo Gen etico com Simulated Annealing e (d) Algoritmo Genético com Busca Local (Memético). Para avaliar os comportamentos computacionais das heurísticas, considerou-se instâncias de diferentes formas com variações nas geometrias e area de plantio. Adicionalmente, uma aplicação destes métodos para um...
The environmental degradation that has occurred throughout the world claims for sustainable and ecological plant production. In this context, agricultural planning based on crop rotation has been addressed in many studies. Once appropriately applied by farmers, this practice brings many bene ts. In fact, it enables biological control of pests, pathogens and weeds, thus reducing the action of pesticides which are harmful to the environment. Planting according to crop rotation also restores the soil, making it always fertile. This thesis presents a binary linear optimization model to the problem of crop rotation aiming to nd a planting schedule for vegetables that maximizes the pro ts of production. The problem constraints include a speci c period for planting each crop, a prede ned demand per crop, the need for green manure and rest period. Other restraints prevent planting of vegetables of the same family consecutively in the same lot, as well as in neighboring lots. A general planting area with irregularly distributed and di erent sized lots is considered. Four metaheuristics were speci cally developed for the above crop rotation problem and the respective algorithms were implemented: (a) a Genetic Algorithm, (b) a Simulated Annealing, and two hybrid approaches - (c) a Genetic Algorithm with Simulated Annealing and (d) a Genetic Algorithm with Local Search, that is, a Memetic algorithm. To evaluate the computing behavior of these algorithms, we considered a crop rotation instance from literature and also an instance built with real data from a Brazilian agricultural company. The computational results showed that the algorithms, specially the hybrid... (Complete abstract click electronic access below)
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Aliano, Filho Angelo. "Metaheurísticas em um problema de rotação de culturas /". Botucatu, 2012. http://hdl.handle.net/11449/95055.
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Orientador: Helenice de Oliveira Florentino SilvaCoorientador: Margarida Vaz Pato
Banca: Fernando Luiz Pio dos Santos
Banca: Silvio Alexandre Araújo
Resumo: Um dos focos centrais na produção vegetal, discutidos ultimamente, e a utilização de medidas que visam um planejamento sustentável e ecológico, tendo em vista a degradação ambiental ocorrida nos ultimos anos. Por este motivo, a Rotação de Culturas tem ganhado destaque na literatura, pois e um meio de produção cujos princípios práticos viabilizam uma agricultura ecológica e produtiva. Esta prática, uma vez bem conduzida pelos agricultores rurais, traz inúmeros benefícios, visto que o controle de pragas, patógenos e de plantas daninhas e realizado biologicamente, diminuindo a ação de pesticidas prejudiciais ao meio ambiente e medidas de recuperação do solo, tornando-o sempre fértil. Nesta dissertação, e apresentado um modelo de otimização 0-1 para o problema de Rotação de Culturas, cujo objetivo foi encontrar uma programação de plantio de hortaliças que maximize o lucro da produção, levando-se em consideração restrições de epoca de semeadura para cada cultura considerada, o não cultivo de plantas de mesma família em lotes vizinhos, proibição de plantio consecutivo de plantas de mesma família botânica em um mesmo lote, a necessidade de adubação verde, período de descanso do solo e de demanda. Nesta modelagem, foi considerada uma area de plantio genérica, cujos lotes são irregularmente distribuídos e de diferentes tamanhos. Para resolução do problema, foram desenvolvidas e implementadas a seguintes metaheurísticas: (a) Algoritmo Gen etico, (b) Simulated Annealing, e as abordagens mistas (c) Algoritmo Gen etico com Simulated Annealing e (d) Algoritmo Genético com Busca Local (Memético). Para avaliar os comportamentos computacionais das heurísticas, considerou-se instâncias de diferentes formas com variações nas geometrias e area de plantio. Adicionalmente, uma aplicação destes métodos para um... (Resumo completo, clicar acesso eletrônico abaixo)
Abstract: The environmental degradation that has occurred throughout the world claims for sustainable and ecological plant production. In this context, agricultural planning based on crop rotation has been addressed in many studies. Once appropriately applied by farmers, this practice brings many bene ts. In fact, it enables biological control of pests, pathogens and weeds, thus reducing the action of pesticides which are harmful to the environment. Planting according to crop rotation also restores the soil, making it always fertile. This thesis presents a binary linear optimization model to the problem of crop rotation aiming to nd a planting schedule for vegetables that maximizes the pro ts of production. The problem constraints include a speci c period for planting each crop, a prede ned demand per crop, the need for green manure and rest period. Other restraints prevent planting of vegetables of the same family consecutively in the same lot, as well as in neighboring lots. A general planting area with irregularly distributed and di erent sized lots is considered. Four metaheuristics were speci cally developed for the above crop rotation problem and the respective algorithms were implemented: (a) a Genetic Algorithm, (b) a Simulated Annealing, and two hybrid approaches - (c) a Genetic Algorithm with Simulated Annealing and (d) a Genetic Algorithm with Local Search, that is, a Memetic algorithm. To evaluate the computing behavior of these algorithms, we considered a crop rotation instance from literature and also an instance built with real data from a Brazilian agricultural company. The computational results showed that the algorithms, specially the hybrid... (Complete abstract click electronic access below)
Mestre
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Hong, Libin. "Hyper-heuristic approaches to automatically designing heuristics as mutation operators for evolutionary programming on function classes". Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/52348/.
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A hyper-heuristic is a search method or learning mechanism for selecting or generating heuristics to solve computational search problems. Researchers classify hyper-heuristics according to the source of feedback during learning: Online learning hyper-heuristics learn while solving a given instance of a problem; Offline learning hyper-heuristics learn from a set of training instances, a method that can generalise to unseen instances. Genetic programming (GP) can be considered a specialization of the more widely known genetic algorithms (GAs) where each individual is a computer program. GP automatically generates computer programs to solve specified tasks. It is a method of searching a space of computer programs. GP can be used as a kind of hyper-heuristic to be a learning algorithm when it uses some feedback from the search process. Our research mainly uses genetic programming as offline hyper-heuristic approach to automatically design various heuristics for evolutionary programming.
Libros sobre el tema "Heuristiek"
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B, Fogel David, ed. How to solve it: Modern heuristics. 2a ed. Berlin: Springer, 2004.
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B, Fogel David, ed. How to solve it: Modern heuristics. Berlin: Springer, 2000.
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Moustakas, Clark E. Heuristic research: Design, methodology, and applications. Newbury Park: Sage Publications, 1990.
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Vanderputten, Steven. Typologie en heuristiek van de bronnen voor de geschiedenis van de middeleeuwen. Gent: Academia Press, 2013.
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Haemers, Jelle, Steven Vanderputten y Tim Soens. Typologie en heuristiek van de bronnen voor de geschiedenis van de middeleeuwen. Gent: Academia, 2011.
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Stiller, Daniela, Katharina Krichel y Wolfgang Schwarz. Heuristik im Mathematikunterricht. Berlin, Heidelberg: Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-63752-4.
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Janonis, Osvaldas. Bibliografinė heuristika. Vilnius: Vilniaus Universiteto leidykla, 1999.
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Osman, Ibrahim H. y James P. Kelly, eds. Meta-Heuristics. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1361-8.
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Clancey, William J. Heuristic classification. [Alexandria, Va.]: DTIC, 1985.
Buscar texto completoCapítulos de libros sobre el tema "Heuristiek"
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Dasgupta, Subrata. "6. Heuristic computing". En Computer Science: A Very Short Introduction, 104–18. Oxford University Press, 2016. http://dx.doi.org/10.1093/actrade/9780198733461.003.0006.
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Many ordinary problems and everyday activities are not conducive to algorithmic solutions. Yet, people do perform these tasks and solve such problems, so what other computational means are available to perform such tasks? The answer is to resort to a mode of computing that deploys heuristics—rules, precepts, principles, hypotheses based on common sense, experience, judgement, analogies, informed guesses, etc., which offer promise but are not guaranteed to solve problems. Heuristic computing encompasses both heuristic search and heuristic algorithms. ‘Heuristic computing’ explains a meta-heuristic called ‘satisficing’; the difference between exact and heuristic algorithms; how heuristics is used in artificial intelligence; weak and strong methods; and how to interpret heuristic rules.
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Pham, Tho Hoan y Tu Bao Ho. "A Hyper-Heuristic for Descriptive Rule Induction". En Data Warehousing and Mining, 3164–75. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-951-9.ch200.
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There are in general three approaches to rule induction: exhaustive search, divide-and conquer, and separate-and-conquer (or its extension as weighted covering). Among them, the third approach, according to different rule search heuristics, can avoid the problem of producing many redundant rules (limitation of the first approach) or non-overlapping rules (limitation of the second approach). In this chapter, we propose a hyper-heuristic to construct rule search heuristics for weighted covering algorithms that allows producing rules of desired generality. The hyper-heuristic is based on a PN space, a new ROC-like tool for analysis, evaluation, and visualization of rules. Well-known rule search heuristics such as entropy, Laplacian, weight relative accuracy, and others are equivalent to ones proposed by the hyper-heuristic. Moreover, it can present new non-linear rule search heuristics, some are especially appropriate for description tasks. The non-linear rule search heuristics have been experimentally compared with others on the generality of rules induced from UCI datasets and used to learn regulatory rules from microarray data.
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"I. Im Moment". En Heuristik, 13–16. transcript-Verlag, 2005. http://dx.doi.org/10.14361/9783839403266-001.
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"II. Heuristik". En Heuristik, 17–19. transcript-Verlag, 2005. http://dx.doi.org/10.14361/9783839403266-002.
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"III. Felt sense". En Heuristik, 20–22. transcript-Verlag, 2005. http://dx.doi.org/10.14361/9783839403266-003.
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"IV. Der persönliche Ton". En Heuristik, 23–25. transcript-Verlag, 2005. http://dx.doi.org/10.14361/9783839403266-004.
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"V. Theorie Erzählung". En Heuristik, 26–28. transcript-Verlag, 2005. http://dx.doi.org/10.14361/9783839403266-005.
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"VI. Wirklichkeit". En Heuristik, 29–30. transcript-Verlag, 2005. http://dx.doi.org/10.14361/9783839403266-006.
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"I. Die Raumerfahrung". En Heuristik, 33–36. transcript-Verlag, 2005. http://dx.doi.org/10.14361/9783839403266-007.
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"II. Studio !K7". En Heuristik, 37–39. transcript-Verlag, 2005. http://dx.doi.org/10.14361/9783839403266-008.
Texto completoActas de conferencias sobre el tema "Heuristiek"
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Puentes, Lucas, Jonathan Cagan y Christopher McComb. "Automated Heuristic Induction From Human Design Data". En ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22151.
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Abstract Through experience, designers develop guiding principles, or heuristics, to aid decision-making in familiar design domains. Generalized versions of common design heuristics have been identified across multiple domains and applied by novices to design problems. Previous work leveraged a sample of these common heuristics to assist in an agent-based design process, which typically lacks heuristics. These predefined heuristics were translated into sequences of specifically applied design changes that followed the theme of the heuristic. To overcome the upfront burden, need for human interpretation, and lack of generality of this manual process, this paper presents a methodology that induces frequent heuristic sequences from an existing timeseries design change dataset. Individual induced sequences are then algorithmically grouped based on similarity to form groups that each represent a shared general heuristic. The heuristic induction methodology is applied to data from two human design studies in different design domains. The first dataset, collected from a truss design task, finds a highly similar set of general heuristics used by human designers to that which was hand selected for the previous computational agent study. The second dataset, collected from a cooling system design problem, demonstrates further applicability and generality of the heuristic induction process. Through this heuristic induction technique, designers working in a specified domain can learn from others’ prior problem-solving strategies and use these strategies in their own future design problems.
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Hitomi, Nozomi y Daniel Selva. "The Effect of Credit Definition and Aggregation Strategies on Multi-Objective Hyper-Heuristics". En ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-47445.
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Heuristics and meta-heuristics are often used to solve complex real-world problems such as the non-linear, non-convex, and multi-objective combinatorial optimization problems that regularly appear in system design and architecture. Unfortunately, the performance of a specific heuristic is largely dependent on the specific problem at hand. Moreover, a heuristic’s performance can vary throughout the optimization process. Hyper-heuristics is one approach that can maintain relatively good performance over the course of an optimization process and across a variety of problems without parameter retuning or major modifications. Given a set of domain-specific and domain-independent heuristics, a hyper-heuristic adapts its search strategy over time by selecting the most promising heuristics to use at a given point. A hyper-heuristic must have: 1) a credit assignment strategy to rank the heuristics by their likelihood of producing improving solutions; and 2) a heuristic selection strategy based on the credits assigned to each heuristic. The literature contains many examples of hyper-heuristics with effective credit assignment and heuristic selection strategies for single-objective optimization problems. In multi-objective optimization problems, however, defining credit is less straightforward because there are often competing objectives. Therefore, there is a need to define and assign credit so that heuristics are rewarded for finding solutions with good trades between the objectives. This paper studies, for the first time, different combinations of credit definition, credit aggregation, and heuristic selection strategies. Credit definitions are based on different applications of the notion of Pareto dominance, namely: A1) dominance of the offspring with respect to the parent solutions; A2) ability to produce non-dominated solutions with respect to the entire population; A3) Pareto ranking with respect to the entire population. Two different credit aggregation strategies for assigning credit are also examined. A heuristic will receive credit for: B1) only the solutions it created in the current iteration or B2) all solutions it created that are in the current population. Different heuristic selection strategies are considered including: C1) probability matching; C2) dynamic multi-armed bandit; and C3) Hyper-GA. Thus, we conduct an experiment with three factors: credit definition (A1, A2, A3), credit aggregation (B1, B2), and heuristic selection (C1, C2, C3) and conduct a full factorial experiment. Performance is measured by hyper-volume of the last population. All algorithms are tested on a design problem for a climate monitoring satellite constellation instead of classical benchmarking problems to apply domain-specific heuristics within the hyper-heuristic.
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Hu, Shuli y Nathan R. Sturtevant. "Direction-Optimizing Breadth-First Search with External Memory Storage". En Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/175.
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While computing resources have continued to grow, methods for building and using large heuristics have not seen significant advances in recent years. We have observed that direction-optimizing breadth-first search, developed for and used broadly in the Graph 500 competition, can also be applied for building heuristics. But, the algorithm cannot run efficiently using external memory -- when the heuristics being built are larger than RAM. This paper shows how to modify direction-optimizing breadth-first search to build external-memory heuristics. We show that the new approach is not effective in state spaces with low asymptotic branching factors, but in other domains we are able to achieve up to a 3x reducing in runtime when building an external-memory heuristic. The approach is then used to build a 2.6TiB Rubik's Cube heuristic with 5.8 trillion entries, the largest pattern database heuristic ever built.
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Trevizan, Felipe, Sylvie Thiébaux y Patrik Haslum. "Operator Counting Heuristics for Probabilistic Planning". En Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/758.
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For the past 25 years, heuristic search has been used to solve domain-independent probabilistic planning problems, but with heuristics that determinise the problem and ignore precious probabilistic information. In this paper, we present a generalization of the operator-counting family of heuristics to Stochastic Shortest Path problems (SSPs) that is able to represent the probability of the actions outcomes. Our experiments show that the equivalent of the net change heuristic in this generalized framework obtains significant run time and coverage improvements over other state-of-the-art heuristics in different planners.
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Cohen, Liron, Tansel Uras, Shiva Jahangiri, Aliyah Arunasalam, Sven Koenig y T. K. Satish Kumar. "The FastMap Algorithm for Shortest Path Computations". En Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/198.
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We present a new preprocessing algorithm for embedding the nodes of a given edge-weighted undirected graph into a Euclidean space. The Euclidean distance between any two nodes in this space approximates the length of the shortest path between them in the given graph. Later, at runtime, a shortest path between any two nodes can be computed with an A* search using the Euclidean distances as heuristic. Our preprocessing algorithm, called FastMap, is inspired by the data-mining algorithm of the same name and runs in near-linear time. Hence, FastMap is orders of magnitude faster than competing approaches that produce a Euclidean embedding using Semidefinite Programming. FastMap also produces admissible and consistent heuristics and therefore guarantees the generation of shortest paths. Moreover, FastMap applies to general undirected graphs for which many traditional heuristics, such as the Manhattan Distance heuristic, are not well defined. Empirically, we demonstrate that A* search using the FastMap heuristic is competitive with A* search using other state-of-the-art heuristics, such as the Differential heuristic.
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Liang, Jia, Hari Govind, Pascal Poupart, Krzysztof Czarnecki y Vijay Ganesh. "An Empirical Study of Branching Heuristics through the Lens of Global Learning Rate". En Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/745.
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In this paper, we analyze a suite of 7 well-known branching heuristics proposed by the SAT community and show that the better heuristics tend to generate more learnt clauses per decision, a metric we define as the global learning rate (GLR). We propose GLR as a metric for the branching heuristic to optimize. We test our hypothesis by developing a new branching heuristic that maximizes GLR greedily. We show empirically that this heuristic achieves very high GLR and interestingly very low literal block distance (LBD) over the learnt clauses. In our experiments this greedy branching heuristic enables the solver to solve instances faster than VSIDS, when the branching time is taken out of the equation. This experiment is a good proof of concept that a branching heuristic maximizing GLR will lead to good solver performance modulo the computational overhead. Finally, we propose a new branching heuristic, called SGDB, that uses machine learning to cheapily approximate greedy maximization of GLR. We show experimentally that SGDB performs on par with the VSIDS branching heuristic.
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Steinmetz, Marcel y Joerg Hoffmann. "LP Heuristics over Conjunctions: Compilation, Convergence, Nogood Learning". En Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/672.
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Two strands of research in classical planning are LP heuristics and conjunctions to improve approximations. Combinations of the two have also been explored. Here, we focus on convergence properties, forcing the LP heuristic to equal the perfect heuristic h* in the limit. We show that, under reasonable assumptions, partial variable merges are strictly dominated by the compilation Pi^C of explicit conjunctions, and that both render the state equation heuristic equal to h* for a suitable set C of conjunctions. We show that consistent potential heuristics can be computed from a variant of Pi^C, and that such heuristics can represent h* for suitable C. As an application of these convergence properties, we consider sound nogood learning in state space search, via refining the set C. We design a suitable refinement method to this end. Experiments on IPC benchmarks show significant performance improvements in several domains.
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Wichlacz, Julia, Daniel Höller y Jörg Hoffmann. "Landmark Heuristics for Lifted Classical Planning". En Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/647.
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While state-of-the-art planning systems need a grounded (propositional) task representation, the input model is provided "lifted", specifying predicates and action schemas with variables over a finite object universe. The size of the grounded model is exponential in predicate/action-schema arity, limiting applicability to cases where it is small enough. Recent work has taken up this challenge, devising an effective lifted forward search planner as basis for lifted heuristic search, as well as a variety of lifted heuristic functions based on the delete relaxation. Here we add a novel family of lifted heuristic functions, based on landmarks. We design two methods for landmark extraction in the lifted setting. The resulting heuristics exhibit performance advantages over previous heuristics in several benchmark domains. Especially the combination with lifted delete relaxation heuristics to a LAMA-style planner yields good results, beating the previous state of the art in lifted planning.
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Renan de Carvalho, Vinicius y Jaime Simão Sichman. "Multi-Agent Election-Based Hyper-Heuristics". En Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/833.
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Hyper-heuristics are high-level methodologies responsible for automatically discover how to combine elements from a low-level heuristic set in order to solve optimization problems. Agents, in turn, are autonomous component responsible for watching an environment and perform some actions according to their perceptions. Thus, agent-based techniques seem suitable for the design of hyper-heuristics. This work presents an agent-based hyper-heuristic framework for choosing the best low-level heuristic. The proposed framework performs a cooperative voting procedure, considering a set of quality indicator voters, to define which multi-objective evolutionary algorithm (MOEA) should generate more new solutions along the execution.
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Mischek, Florian y Nysret Musliu. "Reinforcement Learning for Cross-Domain Hyper-Heuristics". En Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/664.
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In this paper, we propose a new hyper-heuristic approach that uses reinforcement learning to automatically learn the selection of low-level heuristics across a wide range of problem domains. We provide a detailed analysis and evaluation of the algorithm components, including different ways to represent the hyper-heuristic state space and reset strategies to avoid unpromising areas of the solution space. Our methods have been evaluated using HyFlex, a well-known benchmarking framework for cross-domain hyper-heuristics, and compared with state-of-the-art approaches. The experimental evaluation shows that our reinforcement-learning based approach produces results that are competitive with the state-of-the-art, including the top participants of the Cross Domain Hyper-heuristic Search Competition 2011.
Informes sobre el tema "Heuristiek"
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Feigenbaum, Edward A. y Bruce G. Buchanan. Heuristic Programming Project. Fort Belvoir, VA: Defense Technical Information Center, marzo de 1986. http://dx.doi.org/10.21236/ada165995.
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Carter, Lynn. Probability driven heuristic nets. Portland State University Library, enero de 2000. http://dx.doi.org/10.15760/etd.1998.
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Franklin, R. y L. Harmon. Heuristics for Cooperative Problem Solving. Fort Belvoir, VA: Defense Technical Information Center, febrero de 1989. http://dx.doi.org/10.21236/ada206371.
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Pasch, Kenneth A. Heuristics for Job-Shop Scheduling. Fort Belvoir, VA: Defense Technical Information Center, enero de 1988. http://dx.doi.org/10.21236/ada198192.
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Evett, Matthew, James Hendler, Ambuj Mahanti y Dana Nau. PRA: Massively Parallel Heuristic Search. Fort Belvoir, VA: Defense Technical Information Center, enero de 1991. http://dx.doi.org/10.21236/ada454848.
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Kivinen, T. y D. McDonald. Heuristics for Detecting ESP-NULL Packets. RFC Editor, mayo de 2010. http://dx.doi.org/10.17487/rfc5879.
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Hirshleifer, David, Yaron Levi, Ben Lourie y Siew Hong Teoh. Decision Fatigue and Heuristic Analyst Forecasts. Cambridge, MA: National Bureau of Economic Research, febrero de 2018. http://dx.doi.org/10.3386/w24293.
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Skiena, Steven S. Heuristic Approaches to Optimization with Applications. Fort Belvoir, VA: Defense Technical Information Center, agosto de 2001. http://dx.doi.org/10.21236/ada390374.
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Skiena, Steven S. Heuristic Approaches to Optimization With Applications. Fort Belvoir, VA: Defense Technical Information Center, agosto de 2000. http://dx.doi.org/10.21236/ada382413.
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Simon, Luke. Visualization for Hyper-Heuristics: Back-End Processing. Office of Scientific and Technical Information (OSTI), marzo de 2015. http://dx.doi.org/10.2172/1177600.
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