Relevant bibliographies by topics / Timetabling optimization problem

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Timetabling optimization problem'

Author: Grafiati
Published: 4 June 2021
Last updated: 6 February 2022

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Journal articles on the topic "Timetabling optimization problem"

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Chand, A. "A heuristic approach to constraint optimization in timetabling." South Pacific Journal of Natural and Applied Sciences 20, no. 1 (2002): 64. http://dx.doi.org/10.1071/sp02013.

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Timetabling is a difficult (NP-complete) problem and belongs to a general class of problems known as scheduling. Due to a variety of constraints typical in different timetabling environments, it has been difficult to develop a generic solution for timetabling. This paper is an attempt to define a generic computational model for examination timetabling for predefined constraints found in the problem, and proposes a heuristic method of developing an acceptable solution. The declarative nature of the developed constraints language (based on the structured query language) is utilized to construct
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Firdaus Khair, Ahmad, Mokhairi Makhtar, Munirah Mazlan, Mohamad Afendee Mohamed, and Mohd Nordin Abdul Rahman. "A study on university course and exam timetabling problems and methods: an optimization survey." International Journal of Engineering & Technology 7, no. 2.14 (2018): 191. http://dx.doi.org/10.14419/ijet.v7i2.14.12823.

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The objective of this paper was to retrieve the overview approaches that have been proposed and classification constraints related to previ-ous papers of timetabling problems. Optimisation and scheduling are essential problems in every type of timetabling that can be considered as a non-deterministic polynomial. The objective of this paper to investigate the course and exam timetabling problem by presented classifi-cation table of set of constraints and describes the most reliable method that has been used to solve university timetabling problem. The re-sult of study concerned the two most suc
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Ngo, Son Tung, Jafreezal B. Jaafar, Izzatdin Abdul Aziz, Giang Hoang Nguyen, and Anh Ngoc Bui. "Genetic Algorithm for Solving Multi-Objective Optimization in Examination Timetabling Problem." International Journal of Emerging Technologies in Learning (iJET) 16, no. 11 (2021): 4. http://dx.doi.org/10.3991/ijet.v16i11.21017.

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Examination timetabling is one of 3 critical timetabling jobs besides enrollment timetabling and teaching assignment. After a semester, scheduling examinations is not always an easy job in education management, especially for many data. The timetabling problem is an optimization and Np-hard problem. In this study, we build a multi-objective optimizer to create exam schedules for more than 2500 students. Our model aims to optimize the material costs while ensuring the dignity of the exam and students' convenience while considering the rooms' design, the time requirement of each exam, which invo
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Mazlan, Munirah, Mokhairi Makhtar, Ahmad Firdaus Khair Ahmad Khairi, Mohamed Afendee Mohamed, and Mohd Nordin Abdul Rahman. "A study on optimization methods for solving course timetabling problem in university." International Journal of Engineering & Technology 7, no. 2.14 (2018): 196. http://dx.doi.org/10.14419/ijet.v7i2.14.12824.

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Course timetabling is one of the most important processes faced by any educational institution. However, the course timetabling process is time consuming and tiresome as it needs to be done for each regular semester. This paper aims to study on the Optimization methods to solve the course timetabling problem. The study is obtained and discussed by categorizing between the classification of Hard Constraint and Soft Constraint and the classification of Optimization Methods. From the study, it shows that Meta-Heuristics are the mostly method used in solving the course timetabling problem. It is c
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Lei, Yu, and Jiao Shi. "A NNIA Scheme for Timetabling Problems." Journal of Optimization 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/5723239.

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This paper presents a memetic multiobjective optimization algorithm based on NNIA for examination timetabling problems. In this paper, the examination timetabling problem is considered as a two-objective optimization problem while it is modeled as a single-objective optimization problem generally. Within the NNIA framework, the special crossover operator is utilized to search in the solution space; two local search techniques are employed to optimize these two objectives and a diversity-keeping strategy which consists of an elitism group operator and an extension optimization operator to ensur
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Mazlan, Munirah, Mokhairi Makhtar, Ahmad Firdaus Khair Ahmad Khairi, and Mohamad Afendee Mohamed. "University course timetabling model using ant colony optimization algorithm approach." Indonesian Journal of Electrical Engineering and Computer Science 13, no. 1 (2019): 72. http://dx.doi.org/10.11591/ijeecs.v13.i1.pp72-76.

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<p>Due to the increased number of students and regulations, all educational institutions have renewed their interest to appear in the number of complexity and flexibility since the resources and events are becoming more difficult to be scheduled. Timetabling is the type of problems where the events need to be organized into a number of timeslots to prevent the conflicts in using a given set of resources. Thus in the intervening decades, significant progress has been made in the course timetabling problem monitoring with meta-heuristic adjustment. In this study, ant colony optimization (A
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Ma, Xin Min, and Lin Li Wu. "Research on Timetabling Problems Based on Particle Swarm Optimization Algorithm." Advanced Engineering Forum 6-7 (September 2012): 736–41. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.736.

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A new algorithm for timetabling based on particle swarm optimization algorithm was proposed, and the key problems such as particle coding, fitness function fabricating, particle swarm initialization and crossover operation were settled. The fitness value declines when the evolution generation increases. The results showed that it was a good solution for course timetabling problem in the educational system.
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Firdaus Khair, Ahmad, Mokhairi Makhtar, Munirah Mazlan, Mohamad Afendee Mohamed, and Mohd Nordin Abdul Rahman. "Solving examination timetabling problem in UniSZA using ant colony optimization." International Journal of Engineering & Technology 7, no. 2.15 (2018): 132. http://dx.doi.org/10.14419/ijet.v7i2.15.11369.

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At all educational institutions, timetabling is a conventional problem that has always caused numerous difficulties and demands that need to be satisfied. For the examination timetabling problem, those matters can be defined as complexity in scheduling exam events or non-deterministic polynomial hard problems (NP-hard problems). In this study, the latest approach using an ant colony optimisation (ACO) which is the ant system (AS) is presented to find an effective solution for dealing with university exam timetabling problems. This application is believed to be an impressive solution that can b
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Foong, Oi Mean, and Syamilla Bt Rahim. "Particle Swarm Inspired Timetabling for ICT Courses." Applied Mechanics and Materials 263-266 (December 2012): 2138–45. http://dx.doi.org/10.4028/www.scientific.net/amm.263-266.2138.

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University course timetabling is a complex problem which must satisfy a list of constraints in order to allocate the right timeslots and venues for various courses. The challenge is to make the NP-hard problem user-friendly, highly interactive and faster run time complexity of algorithm. The objective of the paper is to propose Particle Swarm Optimization (PSO) timetabling model for Undergraduate Information and Communication Technology (ICT) courses. The PSO model satisfies hard constraints with minimal violation of soft constraints. Empirical results show that the rds: NP hard problem, timet
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Siame, Alinaswe, and Douglas Kunda. "University Course Timetabling using Bayesian based Optimization Algorithm." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 6, no. 2 (2018): 14. http://dx.doi.org/10.3991/ijes.v6i2.8990.

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<p>The timetabling problem has traditionally been treated as a mathematical optimization, heuristic, or human-machine interactive problem. The timetabling problem comprises hard and soft constraints. Hard constraints must be satisfied in order to generate feasible solutions. Soft constraints are sometimes referred to as preferences that can be contravened if necessary. In this research, we present is as both a mathematical and a human-machine problem that requires acceptable and controlled human input, then the algorithm gives options available without conflicting the hard constraints. I
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Dissertations / Theses on the topic "Timetabling optimization problem"

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Ahmad, Maqsood. "Mathematical models and methods based on metaheuristic approach for timetabling problem." Thesis, Clermont-Ferrand 2, 2013. http://www.theses.fr/2013CLF22393/document.

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Résumé indisponible<br>In this thesis we have concerned ourselves with university timetabling problems both course timetabling and examination timetabling problems. Most of the timetabling problems are computationally NP-complete problems, which means that the amount of computation required to find solutions increases exponentially with problem size. These are idiosyncratic nature problems, for example different universities have their own set of constraints, their own definition of good timetable, feasible timetable and their own choice about the use of constraint type (as a soft or hard const
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Wang, Yuqiang. "Models and Algorithms for Some Combinatorial Optimization Problems: University Course Timetabling, Facility Layout and Integrated Production-Distribution Scheduling." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/28757.

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In this dissertation, we address three different combinatorial optimization problems (COPs), each of which has specific real-life applications. Owning to their specific nature, these problems are different from those discussed in the literature. For each of these problems, we present a mathematical programming formulation, analyze the problem to determine its useful, inherent structural properties, and develop an efficient methodology for its solution by exploiting these properties. The first problem that we address is the course timetabling problem encountered at Virginia Tech. The course ti
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Broberg, Felix, and Emelie Eriksson. "Comparing MAX-MIN and Rank-based Ant Colony Optimization Algorithms for solving the University Course Timetabling Problem." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229790.

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The University Course Timetabling Problem (UCTP) is a scheduling problem regarding courses, time slots and rooms, and is often accompanied by a set of feature requirements. As non-trivial instances of the UCTP are NP-hard, traditional computational methods are ineffective. A meta-heuristic alternative is the Ant Colony Optimization (ACO) algorithm, which has previously been proven to successfully solve the UCTP. This paper investigates the relative effectiveness of the MAX-MIN ACO variation to the Rank-based ACO variation on UCTP problem sets of varying difficulty. They are also compared when
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Silva, Odilon Novaes. "Novas estratégias de implementação da meta-heurística VNS aplicada na otimização de grade horária /." Ilha Solteira, 2019. http://hdl.handle.net/11449/181984.

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Orientador: Rubén Augusto Romero Lázaro<br>Resumo: Neste projeto de pesquisa, é abordado o problema otimização de grade horária. O tipo de problema de grade horária abordado é aquele que tem o enunciado e a estrutura de dados apresentado no site da Competição Internacional de Otimização do Problema de Grade Horária. Esse problema pode ser modelado como sendo um problema de Programação Linear Binária de grande porte. Entretanto, os solvers comerciais disponíveis, como o CPLEX, não tem a capacidade de encontrar as soluções ótimas das 20 instâncias mostradas no site da Competição Internacional de
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Francisco, Daniela Oliveira. "Aplicação de algoritmos bio-inspirados ao problema de geração automática de grades horárias." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/18/18153/tde-26082013-104459/.

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A geração de grades horárias de qualidade é um fator crítico em qualquer instituição de ensino, tanto em escolas de ensino fundamental/médio como em universidades. Este problema é considerado complexo, pois devem ser relacionados e otimizados diversos recursos, tais como horários, disciplinas, professores e alunos. Em grande parte das instituições de ensino, a geração de grades horárias é realizada manualmente, o que vem a tornar este processo custoso e sujeito a falhas. Diversas abordagens são também encontradas na literatura para resolução deste problema, nas quais foram aplicados métodos de
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Fischer, Frank. "Dynamic Graph Generation and an Asynchronous Parallel Bundle Method Motivated by Train Timetabling." Doctoral thesis, Universitätsbibliothek Chemnitz, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-118358.

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Lagrangian relaxation is a successful solution approach for many combinatorial optimisation problems, one of them being the train timetabling problem (TTP). We model this problem using time expanded networks for the single train schedules and coupling constraints to enforce restrictions like station capacities and headway times. Lagrangian relaxation of these coupling constraints leads to shortest path subproblems in the time expanded networks and is solved using a proximal bundle method. However, large instances of our practical partner Deutsche Bahn lead to computationally intractable models
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Andary, Philippe. "Optimisation d'emplois du temps par recuit simulé. Algorithmique des algèbres de Lie libres." Rouen, 1996. http://www.theses.fr/1996ROUES001.

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Cette thèse est constituée de deux parties totalement indépendantes. La première partie est consacrée à la réalisation d'un logiciel de calcul automatique d'emploi du temps optimal, par la méthode du recuit simulé. Le premier chapitre introduit la théorie probabiliste sous-jacente : les chaînes de Markov hétérogènes. Puis nous donnons les principaux résultats permettant de valider cette méthode. Dans le second chapitre, nous présentons le logiciel qui a été développé en Common Lisp Object System, sur machine Lisp. Nous formalisons tout d'abord le problème des emplois du temps, puis nous décriv
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Spindler, Morgana. "Uma proposta de solução para problemas de horário educacional utilizando busca dispersa e reconexão por caminhos." Universidade do Vale do Rio do Sinos, 2010. http://www.repositorio.jesuita.org.br/handle/UNISINOS/2284.

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Made available in DSpace on 2015-03-05T14:01:22Z (GMT). No. of bitstreams: 0 Previous issue date: 12<br>Bolsa para curso e programa de Pós Graduação<br>Este trabalho aborda o uso de uma metaheurística populacional para a solução do problema de otimização conhecido, na Pesquisa Operacional, como Programação de Horário de Cursos Baseada em Currículos. O problema de Programação de Horário de Cursos Baseada em Currículos consiste na construção das grades de horário de cursos em instituição de ensino que indicam em quais períodos semanais cada disciplina destes cursos deverá ocorrer, alocando p
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Jang, Shr Yu, and 張士宇. "Genetic Algorithm on the optimization framework of Timetabling problem for University." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/43vup3.

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碩士<br>國立臺北科技大學<br>土木與防災研究所<br>97<br>ABSTRACT Title：Genetic Algorithm on the optimization framework of Pages：100 Timetabling problem for University School：National Taipei University of Technology Time：July, 2009 Degree：Master Researcher：Shr Yu, Jang Advisor：Yu-Chi, Sung Keywords：Genetic Algorithms、School Timetabling Course scheduling is a complicated problem for University which makes administrative personnel feels puzzled in every term. This problem is limited by resource allocation, also belonging to the NP-Complete problem, there are such restrictions on resources as course, teacher, classro
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Huang, Jen-Yu, and 黃任由. "Using parallel ant colony optimization to solve train timetabling problem of mass rapid transit." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/36780033124781548851.

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Book chapters on the topic "Timetabling optimization problem"

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Kostuch, Philipp, and Krzysztof Socha. "Hardness Prediction for the University Course Timetabling Problem." In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24652-7_14.

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Carrasco, Marco P., and Margarida V. Pato. "A Potts Neural Network Heuristic for the Class/Teacher Timetabling Problem." In Applied Optimization. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-4137-7_8.

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Eley, Michael. "Some Experiments with Ant Colony Algorithms for the Exam Timetabling Problem." In Ant Colony Optimization and Swarm Intelligence. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11839088_50.

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Soria-Alcaraz, A. Jorge, Martin Carpio, Hector Puga, et al. "Parallel Meta-heuristic Approaches to the Course Timetabling Problem." In Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17747-2_30.

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Peeters, Leon, and Leo Kroon. "A Cycle Based Optimization Model for the Cyclic Railway Timetabling Problem." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-642-56423-9_16.

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Avella, Pasquale, Maurizio Boccia, Sandro Viglione, and Igor Vasilyev. "A Local Branching MIP Heuristic for a Real-World Curriculum-Based Course Timetabling Problem." In Mathematical Optimization Theory and Operations Research. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33394-2_34.

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Jorge A., Soria-Alcaraz, Carpio Martin, Puga Héctor, Terashima-Marin Hugo, Cruz Reyes Laura, and Sotelo-Figueroa Marco A. "Methodology of Design: A Novel Generic Approach Applied to the Course Timetabling Problem." In Soft Computing Applications in Optimization, Control, and Recognition. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35323-9_12.

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Jat, Sadaf Naseem, and Shengxiang Yang. "A Guided Search Non-dominated Sorting Genetic Algorithm for the Multi-Objective University Course Timetabling Problem." In Evolutionary Computation in Combinatorial Optimization. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20364-0_1.

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Souza, Marcone Jamilson Freitas, Nelson Maculan, and Luis Satoru Ochi. "A GRASP-Tabu Search Algorithm for Solving School Timetabling Problems." In Applied Optimization. Springer US, 2003. http://dx.doi.org/10.1007/978-1-4757-4137-7_31.

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Sabar, Nasser R., Masri Ayob, Graham Kendall, and Rong Qu. "Roulette Wheel Graph Colouring for Solving Examination Timetabling Problems." In Combinatorial Optimization and Applications. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02026-1_44.

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Conference papers on the topic "Timetabling optimization problem"

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Jaradat, Ghaith M., and Masri Ayob. "Scatter search for solving the course timetabling problem." In 2011 3rd Conference on Data Mining and Optimization (DMO). IEEE, 2011. http://dx.doi.org/10.1109/dmo.2011.5976530.

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Pires, Otto Menegasso, Rafael de Santiago, and Jerusa Marchi. "Two Stage Quantum Optimization for the School Timetabling Problem." In 2021 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2021. http://dx.doi.org/10.1109/cec45853.2021.9504701.

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Shaker, Khalid, Salwani Abdullah, and Arwa Hatem. "A Differential Evolution Algorithm for the University course timetabling problem." In 2012 4th Conference on Data Mining and Optimization (DMO). IEEE, 2012. http://dx.doi.org/10.1109/dmo.2012.6329805.

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Dimitriev, A. P., T. A. Lavina, and A. H. Aleksandrov. "Application of Selection Sequence Optimization Algorithm to University Timetabling Problem." In International Scientific Conference “Digitalization of Education: History, Trends and Prospects” (DETP 2020). Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.200509.100.

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Malik, Ariff Md Ab, Masri Ayob, and Abdul Razak Hamdan. "Iterated two-stage multi-neighbourhood tabu search approach for examination timetabling problem." In 2009 2nd Conference on Data Mining and Optimization. IEEE, 2009. http://dx.doi.org/10.1109/dmo.2009.5341897.

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Malik, Ariff Md Ab, Abdul Kadir Othman, Masri Ayob, and Abdul Razak Hamdan. "Hybrid integrated two-stage multi-neighbourhood tabu search-EMCQ technique for examination timetabling problem." In 2011 3rd Conference on Data Mining and Optimization (DMO). IEEE, 2011. http://dx.doi.org/10.1109/dmo.2011.5976533.

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Jaradat, Ghaith M., and Masri Ayob. "Big Bang-Big Crunch optimization algorithm to solve the course timetabling problem." In 2010 10th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2010. http://dx.doi.org/10.1109/isda.2010.5687114.

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Unprasertporn, Thanawat, and Dome Lohpetch. "An Outperforming Hybrid Discrete Particle Swarm Optimization for Solving the Timetabling Problem." In 2020 12th International Conference on Knowledge and Smart Technology (KST). IEEE, 2020. http://dx.doi.org/10.1109/kst48564.2020.9059349.

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"Hill Climbing versus Genetic Algorithm Optimization in Solving the Examination Timetabling Problem." In International Conference on Operations Research and Enterprise Systems. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004286600430052.

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Bidar, Mahdi, and Malek Mouhoub. "Constraint Solving and Optimization Using Evolutionary Techniques." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/901.

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Constraint Solving and Optimization is very relevant in many real world applications including scheduling, planning, configuration, resource allocation and timetabling. Solving a constraint optimization problem consists of finding an assignment of values to variables that optimizes some defined objective functions, subject to a set of constraints imposed on the problem variables. Due to their high dimensional and exponential search spaces, classical methods are unpractical to tackle these problems. An appropriate alternative is to rely on metaheuristics. My thesis is concerned with investigati
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