Academic literature on the topic 'Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)'
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Journal articles on the topic "Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)"
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Swain, Priyadarshi Tapas Ranjan, and Sandhyarani Biswas. "Selection of Materials Using Multi Criteria Decision Making Method by Considering Physical and Mechanical Properties of Jute/Al2O3 Composites." Applied Mechanics and Materials 592-594 (July 2014): 729–33. http://dx.doi.org/10.4028/www.scientific.net/amm.592-594.729.
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Multi-Criteria Decision Making (MCDM) method plays a key role to find out the best option from all possible alternatives. From different application areas Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is one of the Multi-Criteria Decision Making (MCDM) method to find out the correct result. TOPSIS is a real-world and valuable procedure for ranking and selection of a number of externally determined substitutes through distance measures. In this paper, application of techniques for order preference by similarity of an ideal solution (TOPSIS) method is applied for solving multiple criteria (objective) optimization problem in mechanical and physical properties of jute/Al2O3 fiber based hybrid composites. The best performance value of composite is designed from ideal solution and as well as the worst performance value of composite is designed for negative-ideal solution. The results have demonstrated the model to be both robust and efficient.
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Christine and Halim Agung. "IMPLEMENTATION TECHNIQUE METHOD FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) IN ASSESMENT OF DOG CHARACTERISTICS SYSTEM." Jurnal Terapan Teknologi Informasi 2, no. 2 (April 9, 2019): 171–80. http://dx.doi.org/10.21460/jutei.v2i2.106.
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Dogs are the most populated animals in 2016 according to a survey of pet populations by the UK's association of animal food makers (PFMA). With so many types of dogs and different characteristics, not all humans can choose the type of dog that suits their situation and condition. These non-conformities cause dogs to be dumped on the streets or abandoned without proper care.
Therefore the dog characteristics assessment system is made which aims to facilitate the user in choosing the type of dog that is suitable for the user's situation and condition. This system is made using the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution). This system is based on the data of dogs registered with the AKC (American Kennel Club). This system uses eight criteria, three criteria for the filter process and five criteria for the weighting process. Of the five weighting criteria, there are three cost attributes and two benefit attributes. In the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the longest (farthest) distance from the negative ideal solution.
The results obtained from this assessment system are by theory-based testing 50 times with a 78% suitability match percentage.
The conclusion obtained from this research is the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is quite efficient to be applied in a dog characteristic assessment system
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Christine and Halim Agung. "IMPLEMENTATION TECHNIQUE METHOD FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) IN ASSESMENT OF DOG CHARACTERISTICS SYSTEM." Jurnal Terapan Teknologi Informasi 2, no. 2 (April 9, 2019): 171–80. http://dx.doi.org/10.21460/jutei.2018.22.106.
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Dogs are the most populated animals in 2016 according to a survey of pet populations by the UK's association of animal food makers (PFMA). With so many types of dogs and different characteristics, not all humans can choose the type of dog that suits their situation and condition. These non-conformities cause dogs to be dumped on the streets or abandoned without proper care.
Therefore the dog characteristics assessment system is made which aims to facilitate the user in choosing the type of dog that is suitable for the user's situation and condition. This system is made using the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution). This system is based on the data of dogs registered with the AKC (American Kennel Club). This system uses eight criteria, three criteria for the filter process and five criteria for the weighting process. Of the five weighting criteria, there are three cost attributes and two benefit attributes. In the TOPSIS method (Technique for Order Preference by Similarity to Ideal Solution) uses the principle that the chosen alternative must have the closest distance from the positive ideal solution and the longest (farthest) distance from the negative ideal solution.
The results obtained from this assessment system are by theory-based testing 50 times with a 78% suitability match percentage.
The conclusion obtained from this research is the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method is quite efficient to be applied in a dog characteristic assessment system
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Situmorang, Larisma, and Jijon Raphita Sagala. "Sistem Pendukung Keputusan Pemilihan Tentor Terbaik Dengan Metode Technique For Order Preference By Similarity To Ideal Solution (Topsis)." Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) 3, no. 3 (December 5, 2020): 209–14. http://dx.doi.org/10.32672/jnkti.v3i3.2418.
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Abstrak— Tentor adalah Sumber daya manusia yang merupakan bagian yang sangat terpenting bagi tumbuh kembangnya sebuah Bimbingan Belajar. Bimbingan Belajar yang berkembang dengan baik sangatlah dipengaruhi oleh kualitas sumber daya manusia, yang dalam hal ini adalah tentor yang bekerja di dalam sebuah Bimbingan Belajar tersebut. Oleh karena itu, dilakukan pemilihan tentor terbaik menggunakan Metode sistem Keputusan Pemilihan Tentor Terbaik di Bimbingan Manna adalah Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Sistem Pendukung Keputusan yang dibangun dapat membantu serta memudahkan pihak bimbingan belajar manna terutama ketua dalam mengambil sebuah keputusan pemilihan tentor terbaik yang dirancang dengan aplikasi berbasis website dan dengan database phpmyadmin. Form nilai matrik adalah form yang paling penting, karena didalam form ini dilakukan perhitungan dengan langkah-langkah perhitungan metode Topsis mulai dari awal, Nilai Matrik, Nilai Matrik Normalisasi, Nilai Bobot Normalisasi, Matrik Ideal Positif/Negatif, Jarak Solusi Ideal Positif/Negatif, Nilai Preferensi.
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Gupta, Arun, and Shailendra Kumar. "Flow shop scheduling decisions through Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS)." International Journal of Production Management and Engineering 4, no. 2 (July 13, 2016): 43. http://dx.doi.org/10.4995/ijpme.2016.4102.
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<p>The flow-shop scheduling problem (FSP) has been widely studied in the literature and having a very active research area. Over the last few decades, a number of heuristic/meta-heuristic solution techniques have been developed. Some of these techniques offer excellent effectiveness and efficiency at the expense of substantial implementation efforts and being extremely complicated. This paper brings out the application of a Multi-Criteria Decision Making (MCDM) method known as techniques for order preference by similarity to an ideal solution (TOPSIS) using different weighting schemes in flow-shop environment. The objective function is identification of a job sequence which in turn would have minimum makespan (total job completion time). The application of the proposed method to flow shop scheduling is presented and explained with a numerical example. The results of the proposed TOPSIS based technique of FSP are also compared on the basis of some benchmark problems and found compatible with the results obtained from other standard procedures.</p>
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Kurniawan, Dwi Ely. "PEMILIHAN WISATA MENGGUNAKAN TECHNIQUE FOR ORDER PREFERENCE BY SIMILARITY TO IDEAL SOLUTION (TOPSIS) DENGAN VISUALISASI LOKASI OBJEK." KLIK - KUMPULAN JURNAL ILMU KOMPUTER 5, no. 1 (February 28, 2018): 75. http://dx.doi.org/10.20527/klik.v5i1.132.
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<p><em>Batam is one of the existing city in Riau Islands Province, Indonesia. The amount of tourism potential and strategic location for tourists to come to Batam. But what is being searched is the difficulty of finding a tourist attraction based on certain parameters. To overcome these problems, it takes a technology that provides tourist recommendation map information. This research develops this application to give recommendation of tourism based on certain parameters as needed by using TOPSIS method in Batam City web based. The results of development, the application can run functionally (online), can store the tour data and criteria. It can also do the calculation of attractions based on TOPSIS decision. Users can fill the weight of some parameters of distance, time and cost. In order to provide ease in location visualization, the final result of decision calculation is able to provide tourist information in the form of object location of Google Maps API and a brief description of the tour.</em></p><p><em><strong>Keywords</strong>: location, tourist attraction, decision, TOPSIS</em></p><p><em>Batam merupakan salah satu Kota yang terdapat di Provinsi Kepulauan Riau, Indonesia. Banyaknya potensi pariwisata dan lokasi yang strategis membuat peluang wisatawan untuk datang ke Kota Batam. Namun kendala yang ditemukan adalah sulitnya menemukan objek wisata berdasarkan parameter tertentu. Untuk mengatasi masalah tersebut, maka dibutuhkan sebuah teknologi aplikasi yang menyajikan informasi peta rekomendasi wisata di Kota Batam berbasis web. Penelitian ini mengembangkan aplikasi ini untuk memberikan rekomendasi wisata berdasarkan parameter tertentu sesuai kebutuhan wisatawan dengan menggunakan metode TOPSIS. Hasil pengembangan aplikasi dapat berjalan secara online dapat mengelola data wisata dan data kriteria. Selain itu juga dapat melakukan perhitungan objek wisata berdasarkan keputusan TOPSIS. Pengguna dapat mengisi bobot dari beberapa parameter yaitu waktu, jarak dan biaya. Agar dapat memberikan kemudahan dalam visualisasi lokasi hasil akhir perhitungan keputusan, memberikan informasi wisata berupa lokasi objek dari Google Maps API dan deskripsi singkat wisata tersebut.</em></p><p><em><strong>Kata Kunci</strong>: lokasi, potensi wisata, keputusan, TOPSIS</em></p><p><em><br /></em></p>
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Tri susilo, Andri Anto, and Lukman Sunardi. "SISTEM PENDUKUNG KEPUTUSAN PENERIMAAN POLISI PAMONG PRAJA (POL PP) DENGAN METODE TOPSIS (TECHNIQUE FOR ORDER OF PREFERENCE BY SIMILARITY TO IDEAL SOLUTION)." Jurnal Digital Teknologi Informasi 4, no. 2 (July 22, 2021): 52. http://dx.doi.org/10.32502/digital.v4i2.3543.
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Anggota Satuan Polisi Pamong Praja( Sat Pol PP) sebagai aparat Pemerintah Daerah yang diduduki oleh pegawai negeri sipil dan diberi tugas, tanggung jawab, dan wewenang sesuai dengan peraturan perundang-undangan dalam penegakan Peraturan Daerah dan Peraturan Kepala Daerah, penyelenggaraan ketertiban umum dan ketenteraman serta pelindungan masyarakat. Dalam proses penerimaan anggota Sat Pol PP melalui mekanisme tenaga kontrak terdapat beberapa kendala yang dihadapi yaitu belum adanya sistem yang dapat digunakan untuk mengolah data calon anggota Sat Pol PP dan harus mengkalkulasi hasil penilaian calon tenaga Sat Pol PP secara manual. Metode pendukung keputusan dalam penelitian ini adalah TOPSIS (TECHNIQUE FOR ORDER OF PREFERENCE BY SIMILARITY TO IDEAL SOLUTION). Hasil dari penelitian adalah Sistem Pendukung Keputusan Seleksi Penerimaan Tenaga Kontrak Polisi Pamong Praja (Pol PP) dengan Metode TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) Di Kota Lubuklinggau
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Okul, Deniz, Cevriye Gencer, and Emel Kizilkaya Aydogan. "A Method Based on SMAA-Topsis for Stochastic Multi-Criteria Decision Making and a Real-World Application." International Journal of Information Technology & Decision Making 13, no. 05 (September 2014): 957–78. http://dx.doi.org/10.1142/s0219622014500175.
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Stochastic multi-criteria acceptability analysis (SMAA-2) and the technique for order preference by similarity to ideal solution (TOPSIS) are methods for evaluating alternatives with multiple criteria. SMAA is a method that is used for solving multi-criteria decision-making problems with uncertain, inaccurate information, and does not require preference information from the decision makers. The TOPSIS method is based on the principle of determining a solution with the shortest distance to the ideal solution and the greatest distance from the negative-ideal solution. This paper proposes a new method, SMAA-TOPSIS, by combining the SMAA and TOPSIS methods. The SMAA-TOPSIS method was executed for two problems: drug benefit-risk analysis and machine gun selection. This paper found that TOPSIS could be used with uncertain and arbitrarily distributed values for weights and criteria measurements by using a combination of SMAA and TOPSIS. Also, we obtained clearer and consistent SMAA outputs.
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Abbaspour, Asghar, Mahnaz Saremi, Ahmad Alibabaei, and Pedram S. Moghanlu. "Determining the optimal human reliability analysis (HRA) method in healthcare systems using Fuzzy ANP and Fuzzy TOPSIS." Journal of Patient Safety and Risk Management 25, no. 3 (January 23, 2020): 123–33. http://dx.doi.org/10.1177/2516043519900431.
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Purpose As one of the leading causes of deaths and injuries, medical errors constitute a veritable threat to patient safety. Despite this fact, no unique method has yet been established to identify and evaluate medical errors. This study was conducted to select an optimal human reliability analysis method compatible with healthcare systems from available methods. Design/methodology/approach: In order to select the optimal method for the identification and evaluation of medical errors, different criteria and sub-criteria were determined by reviewing the literature and based on experts’ opinions. Next, weights of criteria and sub-criteria were specified by using the fuzzy analytical network process (ANP). Finally, fuzzy technique for order preference by similarity to ideal solution method was used to prioritize the methods. Findings Six criteria and 21 sub-criteria for choosing the optimal method were determined. The utility, usability, and structure of a method had the highest influence with weights of 0.262, 0.191, and 0.187, respectively. Based on the results of fuzzy technique for order preference by similarity to ideal solution, the Human Error Assessment and Reduction Technique method with a closeness coefficient of 0.576 was selected as the optimal method for identifying medical errors. The Human Factors Analysis and Classification System and Systematic Human Error Reduction and Prediction Approach methods ranked second and third, respectively. Originality/value: To date, no studies have attempted to determine the optimal methods for identification and assessment of medical errors. This paper aimed to fill this gap by using fuzzy analytical network process and fuzzy technique for order preference by similarity to ideal solution techniques.
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Andi Dwi Pangestu. "SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN KARYAWAN BERPRESTASI MENGGUNAKAN METODE AHP DAN TOPSIS : STUDI KASUS PT. TELKOM DIVISI ENTERPRISE SERVICE." Jurnal Indonesia Sosial Teknologi 1, no. 4 (November 21, 2020): 244–52. http://dx.doi.org/10.36418/jist.v1i4.36.
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Penentuan karyawan berprestasi pada PT. Telkom Divisi Enterprise Service dilakukan dengan cara memilih karyawan tiap bagian bidang kerja berdasarkan kriteria yang sudah ditentukan. Kriteria-kriteria yang digunakan adalah keterampilan, pengetahuan, keahlian, fleksibilitas, komunikasi, disiplin, tanggung jawab, loyalitas dan kredibilitas. Masalah yang dihadapi oleh perusahaan tersebut adalah bagaimana menentukan karyawan berprestasi dari sejumlah alternatif karyawan. Sistem ini merupakan Sistem Pendukung Keputusan (SPK) yang dibangun dengan menggunakan penggabungan metode Analitycal Hierarchi Process (AHP) dan Technique for Order Preference by Similarity to Ideal (TOPSIS) membantu penentuan karyawan berprestasi. AHP merupakan suatu metode pengambilan keputusan untuk menyelesaikan masalah penentuan pilihan yang sifatnya multiobjective dan metode Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) merupakan suatu bentuk metode pendukung keputusan yang didasarkan pada konsep bahwa alternatif yang terbaik tidak hanya memiliki jarak terpendek dari solusi ideal positif tetapi juga memiliki jarak terpanjang dari solusi ideal negatif. Pembobotan kriteria dilakukan dengan menggunakan AHP dan perankingannya dilakukan dengan menggunakan TOPSIS.
Dissertations / Theses on the topic "Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)"
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Aires, Renan Felinto de Farias. "Revers?o de ordem no m?todo Technique for Order Preference by Similarity to Ideal Solution - TOPSIS." PROGRAMA DE P?S-GRADUA??O EM ADMINISTRA??O, 2017. https://repositorio.ufrn.br/jspui/handle/123456789/24358.
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Durante as ?ltimas d?cadas, v?rios m?todos de Apoio Multicrit?rio ? Decis?o (MCDM) t?m sido utilizados para auxiliar decisores na sele??o de melhores alternativas para problemas de decis?o diversos. Dentre eles, o Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) ? um dos mais utilizados. Apesar da sua grande difus?o, este tem sido criticado devido ? ocorr?ncia de um problema chamado rank reversal (revers?o de ordena??o), que, em sua mais conhecida denomina??o, se refere ? mudan?a na ordena??o de um grupo de alternativas anteriormente ordenadas ap?s uma alternativa irrelevante ter sido adicionada ou exclu?da desse grupo. Apesar da quantidade significativa de estudos sobre este problema para os m?todos MCDM, tem-se que a an?lise desse problema para o TOPSIS ainda ? feita de forma superficial, sem um estudo criterioso acerca das causas e condi??es de ocorr?ncia, bem como marcada por proposi??es de modelos inadequados. Por conta disso, o objetivo desse estudo foi propor uma extens?o do m?todo TOPSIS para minimizar a revers?o de ordena??o. Para isso, foi realizada uma pesquisa experimental a partir de simula??es computacionais geradas aleatoriamente com base em quatro situa??es de revers?o selecionados na literatura. Nos casos de ambas as problem?ticas investigadas, de escolha e de ordena??o, foram analisados os efeitos da normaliza??o utilizada e dos limiares de indiferen?a. Adicionalmente, os casos da problem?tica de escolha tamb?m foram analisados a partir da regress?o log?stica, no intuito de estimar as condi??es em que h? uma maior probabilidade de ocorr?ncia de revers?o de ordena??o. Com base nos experimentos e na an?lise dos modelos da literatura, foi proposta uma extens?o do TOPSIS. O modelo proposto ? baseado na defini??o de um conjunto de valores intitulado de Dom?nio, que representa os valores limites de cada crit?rio na matriz de decis?o no intuito de ultrapassar os inconvenientes do TOPSIS. Para a valida??o da proposta, foi realizada uma aplica??o num?rica para a problem?tica de sele??o de estudantes e concluiu-se que o modelo proposto ? robusto por, simultaneamente, evitar a ocorr?ncia da revers?o de ordena??o e apresentar uma boa capacidade discriminat?ria.
During the last decades, various multi-criteria decision-making methods (MCDM) have been used to assist decision makers in selecting the best alternatives for many decision problems. Among them, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is one of the most used. Despite its wide dissemination, it has been criticized due to the occurrence of a problem called rank reversal, which in its most known meaning refers to the change in the ordering of a group of previously ordered alternatives after an irrelevant alternative has been added or removed from this group. Despite the significant amount of research on this problem for MCDM methods, it has been superficially analyzed in the case of TOPSIS, without a careful study on the occurrence causes and conditions, as well as marked by propositions inadequate models. Therefore, the aim of this study was to propose an extension of the TOPSIS method to minimize rank reversal. For this, it was realized an experimental research through computer simulations randomly generated based on four reversal situations selected in the literature. In the cases of the both problems types investigated, of choice and rank, the effects of the normalization used and the indifference thresholds were analyzed. In addition, the cases of the problem of choice were also analyzed from the logistic regression, in order to estimate the conditions in which there is a greater probability of occurrence of rank reversal. Based on the experiments and analysis of the literature models, an extension of TOPSIS was proposed. The proposed model is based on the definition of a set of values called Domain, which represents the limit values of each criterion in the decision matrix in order to overcome the drawbacks of TOPSIS. For the validation of the proposal, a numerical application was made for the problem of student selection and it was concluded that the proposed model is robust because it simultaneously prevents the occurrence of ranking reversal and presents a good discriminatory capacity.
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Yu, Jodie Wei. "Investigation of New Forward Osmosis Draw Agents and Prioritization of Recent Developments of Draw Agents Using Multi-criteria Decision Analysis." DigitalCommons@CalPoly, 2020. https://digitalcommons.calpoly.edu/theses/2185.
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Forward osmosis (FO) is an emerging technology for water treatment due to their ability to draw freshwater using an osmotic pressure gradient across a semi-permeable membrane. However, the lack of draw agents that could both produce reasonable flux and be separated from the draw solution at a low cost stand in the way of widespread implementation. This study had two objectives: evaluate the performance of three materials — peptone, carboxymethyl cellulose (CMC), and magnetite nanoparticles (Fe3O4 NPs) — as potential draw agents, and to use multi-criteria decision matrices to systematically prioritize known draw agents from literature for research investigation. Peptone showed water flux and reverse solute flux values comparable to other organic draw agents. CMC’s high viscosity made it impractical to use and is not recommended as a draw agent. Fe3O4 NPs showed average low fluxes (e.g., 2.14 LMH) but discrete occurrences of high flux values (e.g., 14 LMH) were observed during FO tests. This result indicates that these nanoparticles have potential as draw agents but further work is needed to optimize the characteristics of the nanoparticle suspension. Separation of the nanoparticles from the product water using coagulation was shown to be theoretically possible if only electrostatic and van der Waals forces are taken into account, not steric repulsion. If coagulation is to be considered for separation, research efforts on development of nanoparticle suspensions as FO draw agents should focus on development of electrostatically stabilized nanoparticles. A combination of Fe3O4 NP and peptone showed a higher flux than Fe3O4 NPs alone, but did not produce additive or synergistic flux. This warrants further research to investigate more combinations of draw agents to achieve higher flux than that obtained by individual draw agents.
Potential draw agents were prioritized by conducting a literature review of draw agents, extracting data on evaluation criteria for draw agents developed over the past five years, using these data to rank the draw agents using the Analytical Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solutions (TOPSIS). The evaluation criteria used in the ranking matrices were water flux, reverse solute flux, replenishment cost, regeneration cost, and regeneration efficacy. The results showed that the top five ranked draw agents were P-2SO3-2Na, TPHMP-Na, PEI-600P-Na, NaCl, and NH4-CO2. The impact of the assumption made during the multi-criteria decision analysis process was evaluated through sensitivity analyses altering criterion weighting and including more criteria. This ranking system provided recommendations for future research and development on draw agents by highlighting research gaps.
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Saksrisathaporn, Krittiya. "A multi-criteria decision support system using knowledge management and project life cycle approach : application to humanitarian supply chain management." Thesis, Lyon 2, 2015. http://www.theses.fr/2015LYO22016/document.
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Cette thèse vise à contribuer à la compréhension des cycle de vie d’une opération humanitaire (HOLC). Gestion de la chaîne d'approvisionnement humanitaire (HSCM) dans un contexte de mise en perspective et dans l’objectif de proposer un modèle décisionnel qui s'applique aux phases de HOLC lors d’une situation réelle. Cela inclut la mise en oeuvre du modèle proposé pour concevoir et développer un outil d'aide à la décision afin d'améliorer les performances de la logistique humanitaire tant dans les opérations de secours nationaux qu’internationaux.Cette recherche est divisée en trois phases. La première partie vise à présenter le sens de l'étude ; la zone de recherche prise en compte pour la gestion de la chaîne d'approvisionnement (SCM) doit être clairement définie. La première phase consiste à clarifier et définir le HSCM HL, la gestion de la chaîne d'approvisionnement commerciale (CSCM) et le SCM, ainsi que la relation entre ces différents éléments. La gestion du cycle de vie du projet (PLCM) et les différentes approches sont également présentés. La compréhension de la différence entre la gestion du cycle de vie du projet (PLM) et la PLCM est également nécessaire, cela ne peut être abordé dans la phase de cycle de vie de l'opération humanitaire. De plus, les modèles Multiple-Criteria Decision Making (MCDM) et l’aide à la décision concernant le HL sont analysés pour établir le fossé existant en matière de recherche. Les approches MCDM qui mettent en oeuvre le système d'aide à la décision (DSS) et la manière dont le MAS a été utilisé dans le contexte HSCM sont étudiées.La deuxième phase consiste en la proposition d’un modèle décisionnel fondé sur l’approche MCDM à l'appui de la décision du décideur avant qu'il/elle prenne des mesures. Ce modèle prévoit le classement des alternatives concernant l'entrepôt, le fournisseur et le transport au cours des phases de HOLC. Le modèle décisionnel proposé est réalisée en 3 scénarios. I. La décision en 4phases HOLC – opération de secours internationale de la Croix-Rouge Française (CRF). II. La décision en3phases HOLC – opération nationale dela Croix-Rouge thaïlandaise (TRC). III. La décision au niveau de la phase de réponse HOLC – opération internationale du TRC dans quatre pays. Dans cette phase, le scénario I et II sont réalisés étape par étape au travers de calculs numériques et formules mathématiques. Le scénario III sera présenté dans la troisième phase. Pour établir trois scénarios, les données internes recueillies lors des entretiens avec le chef de la logistique de la Croix-Rouge Française, et le vice-président de la fondation de la Coix-Rouge thaïlandaise, seront utilisées. Les données externes proviennent de chercheurs qui sont des experts dans le domaine HL ou le champ du HSCM, de la littérature, et de sources issues des organismes humanitaires (documents d’ateliers, rapports, informations publiées sur leurs sites officiels).Dans la troisième phase, une application Internet multi-critères (decision support system MCDSS WB) mettant en oeuvre le modèle proposé est élaborée. Afin d'atteindre une décision appropriée en temps réel, le WB-MCDSS est développé sur la base d’un protocole client-serveur et est simple à utiliser. Le dernier mais non le moindre ; une application de validation du modèle est réalisée à l'aide de l'approche de l'analyse de sensibilitéThis thesis aims to contribute to the understanding of HOLC in context of the HSCM and to propose a decision model which applies to the phases of HOLC the decision making regarding a real situation . This include the implementation of the proposed model to design and develop a decision support tool in order to improve the performance of humanitarian logistics in both national and international relief operations.This research is divided into three phases; the first phase is to clarify and define HL among HSCM, commercial supply chain management (CSCM) and SCM and their relationship. Project Life Cycle Management (PLCM) approaches are also presented. The difference between project life cycle management (PLM) and PLCM is also required to distinguish a clear understanding which can be addressed in the phase of humanitarian operation life cycle. Additionally, the literature of Multiple-Criteria Decision Making (MCDM) models and existing decision aid system for HL are analyzed to establish the research gap. The MCDM approaches which implement the decision support system (DSS) and lastly how DSS has been used in the HSCM context.The second phase is to propose a decision model based on MCDM approaches to support the decision of the decision maker before he/she takes action. This model provides the ranking alternatives to warehouse, supplier and transportation over the phases of HOLC. The proposed decision model is conducted in 3 scenarios; I. The decision in 4-phase HOLC, international relief operation of French Red Cross (FRC). II. The decision on 3-phase HOLC, national operation by the Thai Red Cross (TRC). III. The decision on response phase HOLC, international operation by the FRC in four countries. In this phase, the scenario I and II are performed step by step though numerical calculation and mathematical formulas. The scenario III will be presented in the third phase.In the third phase, an application of web-based multi-criteria decision support system (WB-MCDSS) which implement the proposed model is developed. The web-based multi-criteria decision support system is developed based on the integration of analytical hierarchy process (AHP) and TOPSIS approaches. In order to achieve an appropriate decision in a real time response, the WB-MCDSS is developed based on server-client protocol and is simple to operate. Last but not least, a validation application of the model is performed using the sensitivity analysis approach
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Fallas, Valverde Paula Daniela. "Improving efficiency in logistics operations of the wood fiber supply chain." Thesis, Virginia Tech, 2019. http://hdl.handle.net/10919/88797.
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There is a gap in the research regarding applications of Lean tools in the wood fiber supply chain. A Value Stream Map (VSM) tool that focused on identifying Lean waste in logistic operations was developed and applied to three case study firms: a paper mill, a sawmill, and a logger. Using the VSM tool an absence of structured methods to select and assess suppliers was found, which promotes a fluctuating environment for suppliers. Therefore, a tool that implements a hierarchy system to categorize suppliers was developed, verified and validated. Through the use of the VSM implementation the author found a lack of information sharing between supply chain stakeholders, which causes a reactive environment for the industry. Improvements in wood flow planning, tract allocation, truck scheduling, and communication were projected as a future state of the system. The annual potential savings by implementing the projected improvements in the total cost were as follows for the paper mill, the sawmill, and the logger respectively: $306,232, $312,085, $756,504. As a result of the findings obtained through the VSMs, a supplier selection model was designed. The tool was implemented into software for the wood industry. The tool was then verified and validated. The verification process consisted of comparing the output through previously known results and was performed through seven interviews with different stakeholders. The appropriate application of the supplier selection tool improves the way in which companies in the wood industry select and assess their suppliers and guarantee that the best alternatives are selected.Master of Science
In the wood fiber supply chain, integration between different parties within a supply chain has proven to be a difficult task. An innovative lean-logistics tool value-streamed map (VSM) was developed to evaluate the current and future state of a supply chain Once the tool was developed it was used to map the wood fiber supply chain, determine and measure key performance metrics, calculate the cost of logistics operations, and identify potential sources of waste. Three case studies representing common wood fiber supply chains were conducted to develop three current VSMs for selected value streams. The lack of communication between supply chain partners was determined to be the most significant source of waste in all three cases. Lack of communication could lead to idle equipment, unnecessary waiting times, excessive inventories, overproduction, and excessive transportation and movement. As a result of the findings obtained through the VSMs, which revealed the absence of structured methods to select and assess suppliers, a supplier selection model was designed. The tool was implemented into software for the wood industry. The tool was then verified and validated. The verification process consisted of comparing the output through previously known results and was performed through seven interviews with different stakeholders. The appropriate application of the supplier selection tool improves the way in which companies in the wood industry select and assess their suppliers and guarantee that the best alternatives are selected, thus increasing the chance of a successful relationship and increasing the value that the company gets from its supplier base.
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YANG, TSANG-HUNG, and 楊璨鴻. "Research on Multiple Criteria Decision Making Using Technique for Order Preference by Similarity to Ideal Solution." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/dcs3jq.
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碩士南開科技大學
電子工程研究所
106
The purpose of this study was to investigate the optimal warranty plan for the base segment of the Centrino Project CM32 mounted combat vehicle. The scope of research was limited to three sub-systems such as transmission, steering and load bearing under the chassis system. And in the military peacekeeping or business model design, we suggest three different base warranty programs. After the study of guidelines, literature analysis, and renovation work flow, this paper proposes guidelines for the development of three factors: technical energy, hardware facilities, and cost-effectiveness, including battle training support capabilities, assembly renovation capabilities, system integration capabilities, full vehicle testing capabilities, machine tool energy, plant space size, site location selection, personnel costs, facility maintenance costs and administrative costs.According to the design of the questionnaire and implementation of expert selection operations, the final search related opinions are converted into quantitative values. After the numerical calculation was performed using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), the best plan was selected. This study uses an objective research method to perform numerical analysis. The results can be used as a reference for policy makers in subsequent policy development.
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TSAI, KUO-SHU, and 蔡國書. "A Study of Using Technique for Order Preference by Similarity to Ideal Solution to Evaluate Building Energy Performance." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/uwzvx9.
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碩士國立臺北科技大學
能源與冷凍空調工程系
106
In recent years, faced with global warming and energy shortage, the low-carbon economic development mode based on low power consumption, low emission and low pollution has become a popular topic studied by many countries. Therefore, it is very important to analyze low-carbon economic development level, and learn about the low-carbon development situation to provide decision reference frame for establishing suitable characteristic low-carbon development modes. At present, the common methods for evaluating energy user performance mostly use EUI as reference indicator. This study uses multiple criteria evaluation theory, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is combined with the powerful drawing and computational analysis functions of R software, for its free and extensive functions, it is used in finance industry, traffic transport industry, medical industry and so on, but seldom used in building energy consumption analysis. The analysis method of TOPSIS is used to analyze the energy utilization efficiency of the branches of a securities company in the whole province, to discuss the performance of research subject. The multi-indicator ranking is performed, the clustering results are similar. This method can evaluate the energy use performance more effectively. The feasibility of the method is confirmed by case analysis. The evaluated unit to be improved may be found more accurately by coordinating the efficiency indicators. The results of this study can provide objective and effective criteria for decision making related persons, the differences in the energy utilization efficiency are discussed, so as to obtain the potential energy saving space of building and improvement method which are provided for the future studies.
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LIN, Chun-peng, and 林俊朋. "The Application of Conjoint Analysis and Technique for Order Preference by Similarity to Ideal Solution in Product Design Concept Development." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/65679316835107019964.
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碩士國立成功大學
工業設計學系碩博士班
95
Nowadays in a quick-developed product world, a new successful design should match customer’s requirement and enterprise’s criteria. For designers to comprehend the customer’s requirement and enterprise’s criteria has become an important issue. Today, in the study of product development, most only consider one party of requirement. But by only considering one party of requirement, the result of study is not satisfying. And that can’t tell us if the product match customer’s requirement and enterprise’s criteria or not. Therefore, we would like to develop an aided-concept development system which combines the design method, to help designers to design products. In the study, we take cutter design as example. We use conjoint analysis to find out customer’s preference, and make a concept design to satisfy customers. And we use nominal group technique (NGT) and analytic network process (ANP) to get weight of enterprise’s criteria. Finally, we order preference by similarity to ideal solution (TOPSIS) to evaluate that concept which can satisfy customer’s requirement of vendor’s criteria. In this case, the result of the customer’s requirement and of enterprise’s criteria is different. Through the procedure structure of this research can obtain an equalization point and produce the concept motion that can meet consumers and enterprise's operator at the same time. The result of study shows the structure of this research of the effect which develops the stationery products penknife designing: 1.Shorten the time of developing design concept. 2.Effective and clear to learn the pluses and minuses of design concept, and improving it. 3.Reduce the probability of developing wrong products of enterprises. Keyword： Conjoint Analysis,Nominal Group Technique (NGT), Analytic Network Process (ANP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).
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Yu, Pi-Chun, and 游筆鈞. "Adapted to Tie Fixture Style as Technique for Order Preference by Similarity to Ideal Solution Method in Construction of Decision Model." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/62671753449305045047.
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碩士國立成功大學
工業設計學系碩博士班
94
As the development of computer software and internet matures, the consuming lifestyle is also changes.When choosing a product, consumers often face the problem of not being able to choose the product they want due to the large number of products available. Even so, when comparing a product’s differentstyles, the imagery of a product cannot fulfill the best evaluation of all the different styles. Because product stylization has repulsion, opposition and relation so each style’s evaluation cannot reach its best ratings. This research uses the priority and preferences of the consumer to reach the best product arrangement that fulfills the expectation of the consumer. This research uses TOPSIS (Technique for Order Preference by Similarity to Ideal Solution Method) to develop a product style strategic decision mode. This is done through the preferred style of the consumer to find the appropriate product suggestion. In TOPSIS, its principle is to give the consumer priorities and uses the differences between them to calculate the best scheme. This is applied to the selection of a tie through peculiarity and opposition, and through the allocation of the priorities, the final ranking is suggested. When formulating the structure of this strategic decision method, this research uses the example ofmatching shirts and ties, and researches on both the colors of a tie and a shirt with the patterns on the tie. Through interviews with experts and data collection, Focus Group is proceeded to sum up each components and benchmark numbers of the experiment. Image composition technique is also used to present different combinations of the ties and shirts, in terms of colors and patterns. Prior to the experiment, KJ method (Kawakita Jiro) is applied to group vocabularies of each style combinations. Four final opposing imagery vocabularies are formed. Throughout the experiment, Semantic Differences are applied to each parameter combination to find out the influence of each composed image, and four sets of style vocabularies are evaluated. Consumers only have to choose their favorite styles in each applicable image vocabularies and provide the priority of each style for TOPSIS to come up with a favorable tie and shirt ranking.
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Hui-MeiLin and 林惠美. "Supplier Selection for the Components of New Product by Case-Based Reasoning and Technique for Order Preference by Similarity to Ideal Solution." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/95632073689047580154.
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碩士國立成功大學
工業與資訊管理學系專班
101
Supplier selection is one of the most important jobs of supply chain management. Because of the reducing of product life cycle, manufacturers have to utilize the existing supply chain to shorten the time from design to market as well as improve their competition. In fact, buyers will nominate the potential suppliers by their expertise and experience to decide the most appropriate candidates based on the RFQ (request for quotation) and negotiation result. However, different buyers lead to different potential supplier list and supplier evaluation outcomes. Therefore, it becomes an important issue to find the most appropriate supplier regardless of the differences of the expertise and experience of buyers. Similar to the purchasing process, we propose a two-stage method for supplier selection. The first stage employs the case-based reasoning method to find potential suppliers by calculating the cosine similarity of new material description with the old ones stored in a database. Then the technique for order preference by similarity to ideal solution (TOPSIS) is used in the second stage to rank the potential suppliers by their performance that is evaluated by the following factors: quality, delivery, cost, and supply possibility. The weights of the factors are set up in advance by decision makers. For the case analyzed in this study, the most appropriate supplier determined by the TOPSIS method is identical to the one suggested by a senior professional buyer. This demonstrates that the method proposed by this study can be helpful to the buyers for supplier selection.
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Liu, Shih-Wen, and 劉時玟. "A model using Fuzzy Analytic Hierarchy Process and Fuzzy Technique for Order Preference by Similarity to Ideal Solution for selecting Light Emitting Diode companies." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/46874533292994655981.
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碩士國立勤益科技大學
工業工程與管理系
99
In recent years, global environmental issues become more popular, in order to improve the global warming problems, people should actively use energy-efficient products.At present, Green industries including Sloar power, Wind energy, Hydroelectric and LED (Light Emitting Diode) products. Nowadays LED industry has been developed for almost 30 years in Taiwan. Today, LED industry in Taiwan has a complete supply chain from suppliers to retailers. How to select a LED packaging supplier that meets the requirements in quality, delivery, cost, risk and R&D is important for competiveness and future potential. Sometimes decision makers cannot make a decisive judgement when the decision dimensions drive to Multi-Criteria. In this paper, we evaluate three LED packaging firms by an evaluation process with two phases. First, we according to questionnaires from experts to calculate the relative weights of the criteria by fuzzy Analytic Network Process (FANP), and we also explain why criteria weights influenced the objective. Then, we select the best supplier from the LED packaging firms by fuzzy technique for order preference by similarity to ideal solution (FTOPSIS).
Book chapters on the topic "Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)"
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Thakkar, Jitesh J. "Technique for Order Preference and Similarity to Ideal Solution (TOPSIS)." In Multi-Criteria Decision Making, 83–91. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4745-8_5.
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Uzun, Berna, Mustapha Taiwo, Aizhan Syidanova, and Dilber Uzun Ozsahin. "The Technique For Order of Preference by Similarity to Ideal Solution (TOPSIS)." In Application of Multi-Criteria Decision Analysis in Environmental and Civil Engineering, 25–30. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-64765-0_4.
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Chen, Junfei, Lu Xia, and Huimin Wang. "Research on Urban Water Security Evaluation Based on Technique for Order Preference by Similarity to Ideal Solution Model." In Computational Risk Management, 341–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18387-4_38.
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Dinçer, Hasan, Ümit Hacıoğlu, and Serhat Yüksel. "Measurement of the Economic Vulnerability Index in the Third World and Emerging Economies: A Comparative Analysis Using Fuzzy Analytical Network Process and Technique for Order Preference by Similarity to an Ideal Solution." In Economic Growth and Demographic Transition in Third World Nations, 436–51. Includes bibliographical references and index.: Apple Academic Press, 2019. http://dx.doi.org/10.1201/9780429433894-24.
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Ghosh, Anindya, Prithwiraj Mal, and Abhijit Majumdar. "Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)." In Advanced Optimization and Decision-Making Techniques in Textile Manufacturing, 35–63. CRC Press, 2019. http://dx.doi.org/10.1201/9780429504419-3.
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Toklu, Merve Cengiz. "The Technique for Order of Preference by Similarity to Ideal Solution Method in Fuzzy Environment." In Multi-Criteria Decision Analysis in Management, 139–68. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2216-5.ch007.
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Decision-making process is the selection of the most appropriate one among the alternatives. Different selection criteria are considered in the decision-making process. Simultaneous assessment of different evaluation criteria may not always be possible. Multi-criteria decision-making techniques provide an easily applicable mathematical solution in this respect. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is one of the multi-criteria decision-making techniques. This method is used in many problems in literature and allows multiple decision makers to choose the most suitable alternative by evaluating them together with different criteria. Assessments of decision makers may include linguistic statements. In this case, the Fuzzy Logic approach can be used. In this chapter, Fuzzy TOPSIS method is explained with a detailed numerical example.
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Wu, Desheng, and David L. Olson. "A TOPSIS Data Mining Demonstration and Application to Credit Scoring." In Data Warehousing and Mining, 1877–87. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-951-9.ch112.
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The technique for order preference by similarity to ideal solution (TOPSIS) is a technique that can consider any number of measures, seeking to identify solutions close to an ideal and far from a nadir solution. TOPSIS has traditionally been applied in multiple criteria decision analysis. In this paper we propose an approach to develop a TOPSIS classifier. We demonstrate its use in credit scoring, providing a way to deal with large sets of data using machine learning. Data sets often contain many potential explanatory variables, some preferably minimized, some preferably maximized. Results are favorable by a comparison with traditional data mining techniques of decision trees. Proposed models are validated using Mont Carlo simulation.
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Roy, Rumi, Surapati Pramanik, and Tapan Kumar Roy. "Interval Rough Neutrosophic TOPSIS Strategy for Multi-Attribute Decision Making." In Neutrosophic Sets in Decision Analysis and Operations Research, 98–118. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-2555-5.ch005.
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In this chapter, the authors present a new strategy for multi-attribute decision making in interval rough neutrosophic environment. They define Hamming distance and Euclidean distance between interval rough neutrosophic numbers. They also define interval rough neutrosophic relative positive ideal solution (IRNRPIS) and interval rough neutrosophic relative negative ideal solution (IRNRNIS). Then the ranking order of the alternatives is obtained by the technique for order preference by similarity to ideal solution (TOPSIS) strategy. Finally, a numerical example is provided to demonstrate the applicability and effectiveness of the proposed interval rough neutrosophic TOPSIS strategy.
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Aruldoss, Martin, Miranda Lakshmi Travis, and Prasanna Venkatesan Venkatasamy. "Identification of User Preference for Multi-Criteria Reporting in Business Intelligence." In Improving E-Commerce Web Applications Through Business Intelligence Techniques, 16–47. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-3646-8.ch002.
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Business intelligence (BI) is an integrated set of tools used to support the transformation of data into information in order to support decision making. Among different functionalities, reporting plays a significant role that provides information to its readers to make better decisions. BI lacks user-specific reporting to the different levels of users of an organization. Different users require different kinds of reporting with respect to different requirement (criteria) in an organization. A multi-criteria reporting (MCR) finds the suitable information to suitable user based on the multiple conflicting preferences of a user. Technique for order preference by similarity to ideal solution (TOPSIS) is the most popularly applied multi-criteria decision-making (MCDM) technique selected to identify different levels of user preference for MCR. Banking business is considered as a case study to identify user preference for MCR. This research also designs evaluation metrics for TOPSIS.
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Prasad, K. G. Durga, B. L. Manasa, P. Krishna Murthy, and K. D. S. Sravani. "QFD-Based TOPSIS Methodology for Material Selection." In Handbook of Research on Developments and Trends in Industrial and Materials Engineering, 169–93. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1831-1.ch008.
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Material selection is one of the interdisciplinary activities involved in product design and development. It is an integral part of concept phase and configuration phase of mechanical design process. Therefore, a successful product design should take into consideration of material properties to meet the design requirements which reflect the expectations of the end users of a product. This chapter presents a user-centered material selection methodology which paves a path for reflecting user preferences into design requirements and then into material selection decision. In the proposed approach, weights of the material selection criteria are obtained through Quality Function Deployment (QFD) and then the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) methodology is employed to achieve the optimum selection of material under a multi-attribute decision-making environment. An illustrative example is taken from the literature and presented in this chapter to demonstrate the proposed methodology.
Conference papers on the topic "Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)"
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Imamah. "Selection of BEM Candidates Using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)." In 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS). IEEE, 2018. http://dx.doi.org/10.1109/eeccis.2018.8693000.
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Shanmuganathan, M., and T. Nalini. "Technique for Order Preference by Similarity to Ideal Solution (Topsis) Applied to Image Fusion -Limitations." In 2021 International Conference on Intelligent Technologies (CONIT). IEEE, 2021. http://dx.doi.org/10.1109/conit51480.2021.9498545.
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Vinícius Gonzaga Alves Araujo, Jonathas, Carlos Francisco Simões Gomes, Andréa Soares Bonifácio, and MARCOS DOS SANTOS. "Uma revisão sistemática do método Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)." In IX Simpósio de Engenharia de Produção - SIMEP 2021. Recife: Even3, 2021. http://dx.doi.org/10.29327/9simep.331708.
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Gupta, Neha, and Yaduvir Singh. "Optimal selection of wind power plant components using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)." In 2016 International Conference on Electrical Power and Energy Systems (ICEPES). IEEE, 2016. http://dx.doi.org/10.1109/icepes.2016.7915949.
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Bansode, Raj, and Sanjaykumar Gangurde. "Shielded Metal Arc Welding Electrode Selection Using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method." In International Conference on Communication and Signal Processing 2016 (ICCASP 2016). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/iccasp-16.2017.3.
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Ishak, Aulia, and Syafiah Parinduri. "Supplier Selection Using Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)." In Proceedings of the 2019 1st International Conference on Engineering and Management in Industrial System (ICOEMIS 2019). Paris, France: Atlantis Press, 2019. http://dx.doi.org/10.2991/icoemis-19.2019.44.
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Göktolga, Ziya Gökalp, Engin Karakış, and Hakan Türkay. "Comparison of the Economic Performance of Turkish Republics in Central Asia with TOPSIS Method." In International Conference on Eurasian Economies. Eurasian Economists Association, 2015. http://dx.doi.org/10.36880/c06.01270.
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The aim of this study is to compare the economic performance of Turkish Republics in Central Asia with Multi Criteria Decision Making (MCDM) methods. Turkish Republics have been experiencing a transition from a centrally planned economy towards a market economy since their independence. In this study important macroeconomic indicators are used to determine economic performance. Economic performance evaluation of the country is an important issue for economic management, investors, creditors and stock investors. Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method outranks the countries according to the proximity of the positive ideal solution and distance of the negative ideal solution. Economic Performance of Turkish Republics in Central Asia (Azerbaijan, Turkmenistan, Kazakhstan, Kyrgyzstan, and Uzbekistan) are compared with TOPSIS method. İnvestigated with TOPSIS method countries best and worst economic performance years are detected during mentioned period and results are analyzed.
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Priadi, Sunni Nugraha, Hadi Ismoyo, and Alexandra Sinta Wahjudewanti. "Non-Simulation Enhanced Oil Recovery Technique Screening in X and Y Fields Using a Combination of Analytical Hierarchy Process and Technique for Order of Preference by Similarity to Ideal Solution." In SPE Annual Technical Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/206320-ms.
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Abstract The X and Y fields are among the oil fields in the Java basin, Indonesia. As oil production decreases due to exploitation activities in X and Y fields, it is necessary to carry out activities to increase production. To increase the yield of its oil production, Enhanced Oil Recovery (EOR) technology is needed. Enhanced oil recovery (EOR) technique screening analysis is needed to be carried out at the initial stage of the feasibility study in the EOR project. At present, there is no fully established method for identifying potential candidates for the EOR technique. The most common approach for selecting EOR techniques is conventional filtering, which is generally based on the "go-no go" trial and error, with a reduced chance of success. Besides, determining potential candidates for EOR techniques often uses a reservoirsimulation approach, but this is time-consuming and requires high costs in using the software license. EOR technique screening with a method that explains how to form a multi-criteria decision-making model with a combination of AHP and TOPSIS methods together as a systematic and measurable method to get the best EOR techniques in both X and Y fields. The research results found that the CO2Immiscible Technique was the most appropriate for EOR in fields X and Y because it has the highest preference value (0.676), is then followed by the Micellar technique (preference value 0.645) and HC Immiscible (preference value 0.517). With the multi-criteria decision-making technique, the best EOR technique results are obtained. Then the proposal can provide valuable recommendations for company management in both fields X and Y with a faster, accurate, and inexpensive method compared to the reservoir simulation method, which has a longer processing time and more expensive costs. This technique can support technology implementation decision-making in the early stages of EOR project development.
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Bottani, Eleonora, Marta Rinaldi, and Federico Solari. "Corporate sustainability assessment through fuzzy TOPSIS." In The 6th International Workshop on Simulation for Energy, Sustainable Development & Environment. CAL-TEK srl, 2018. http://dx.doi.org/10.46354/i3m.2018.sesde.008.
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"The aim of this paper is to propose a decisionmaking methodology that enables the analysis and evaluation of sustainability at the corporate level. The proposed methodology grounds on two tools, namely the technique for order preference by similarity to ideal solution (TOPSIS) approach and fuzzy logic. The integration of these tools offers an effective way to deal with two typical issues of sustainability assessment, i.e.: 1) the fact that the company’s performance should be frequently evaluated against qualitative key performance indicators; and 2) the fact that to be meaningful, the company’s sustainability performance needs to be compared to a reference value, e.g. a threshold or benchmark, to evaluating how the company is distant from a target. The proposed approach has been applied to a real firm, operating in the food machinery industry, for testing purpose. The main pros and cons of the approach are described."
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Haşıloğlu, Selçuk Burak. "Determination of Country of Origin Image with Fuzzy Set Theory." In International Conference on Eurasian Economies. Eurasian Economists Association, 2012. http://dx.doi.org/10.36880/c03.00471.
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As foreign trade has become more spread, the country of production and even the origin of the raw material used in the production has become an important factor. Mentioning the country of origin on the label of the product dates back to World War-I when “Good product sells itself” understanding is dominant. In this study, the image of country of origin was evaluated with fuzzy set theory. Fuzzy sets theory lays foundation for the methods used in the solution of relative and uncertain problems. As image evaluation is a relative issue, these methods were used in our study. The first phase in the study model is data collection. Data collected was used to determine image factors, calculate factor loads (weights) and order alternatives. In the determination of image factors Fuzzy Cognitive Mapping (FCM) method was employed. To calculate factor and alternative weights Fuzzy Analytic Hierarchy Process (AHP) method was used. In the phase of ordering of alternatives which are called product group elements both Fuzzy AHP and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method were employed. TOPSIS is based on the main principle of similarity to ideal solution and is employed to solve problem and make decision. In our study FCM, Fuzzy AHP and TOPSIS methods were used in stages, analyses were performed and solutions were developed. In the final part, there are evaluations with regard to which product group will be more effective when which image is minimized.