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A Hybrid Multi-objective Evolutionary Algorithm for the Uncapacitated Exam Proximity Problem
[chapter]
2005
Lecture Notes in Computer Science
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A hybrid Multi-Objective Evolutionary Algorithm is used to tackle the uncapacitated exam proximity problem. ...
The other search operator implements a simplified Variable Neighborhood Descent meta-heuristic and its role is to improve the proximity cost. ...
Acknowledgements The authors would like to thank the referees for their constructive and helpful advice. ...
doi:10.1007/11593577_17
fatcat:urodoqchlvf6rbt7lb3mfhcsrq
A multiobjective framework for heavily constrained examination timetabling problems
2008
Annals of Operations Research
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The role of the mulitobjective algorithm is to iteratively improve a population of orderings, with respect to the given objectives, using various mutation and reordering heuristics. ...
In this prototype study, we focus on the two objectives: minimizing timetable length while simultaneously optimizing the spread of examinations for individual students. ...
A local search algorithm is then used to reduce conflicts and repair infeasibility. The results obtained in [18] for the uncapacitated problem are used for benchmarking the present study. ...
doi:10.1007/s10479-008-0490-3
fatcat:ka6esn4jmbbzxctcdxft7yjcp4
Investigating Ahuja–Orlin's large neighbourhood search approach for examination timetabling
2006
OR spectrum
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This solution search methodology, originally developed by Ahuja and Orlin, has been applied successfully in the past to a number of difficult combinatorial optimization problems. ...
We have evaluated our approach against the latest methodologies in the literature on standard benchmark problems. We demonstrate that our approach produces some of the best known. ...
We are very grateful for this support. We are also very grateful to the anonymous referees whose thoughtful and considered comments significantly improved the paper. ...
doi:10.1007/s00291-006-0034-7
fatcat:67ehcnwnlnd3re5o6yyyl6gqjm
An informed genetic algorithm for the examination timetabling problem
2010
Applied Soft Computing
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Acknowledgement The authors would like to thank the reviewers for their insightful comments and suggestions. ...
The mutation operator is used to improve timetables. The hybrid multi-objective algorithm (hMOEA) implemented by Cote et al. ...
Paquete and Fonseca use a multi-objective evolutionary algorithm to induce a timetable for the Unit of Exact and Human Sciences of the University of Algarve. ...
doi:10.1016/j.asoc.2009.08.011
fatcat:h7zopddawrdhrd4e4r7qyhqhze
A honey-bee mating optimization algorithm for educational timetabling problems
2012
European Journal of Operational Research
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In this work, we propose a variant of the Honey-bee Mating Optimization Algorithm for solving educational timetabling problems. ...
The performance of the proposed algorithm is tested over two benchmark problems; exam (Carter's un-capacitated datasets) and course (Socha datasets) timetabling problems. ...
Cote et al. (2005) proposed a bi-objective evolutionary algorithm to minimize the timetable length and to space out conflicting exams as much as possible. ...
doi:10.1016/j.ejor.2011.08.006
fatcat:xatycq3kqrcrrlxhbq3swrzs74
Evolving timetabling heuristics using a grammar-based genetic programming hyper-heuristic framework
2009
Memetic Computing
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In other words, the system keeps on evolving heuristics for a problem instance until a good solution is found. ...
The framework is tested on some of the most widely used benchmarks in the field of exam timetabling and compared with the best state-of-the-art approaches. ...
A hybrid multi-objective evolutionary algorithm was presented in [24] . The framework was used to tackle the uncapacitated exam proximity problem. ...
doi:10.1007/s12293-009-0022-y
fatcat:35kg7q6fg5b5rangj3kquynsjy
Grammatical Evolution Hyper-Heuristic for Combinatorial Optimization Problems
2013
IEEE Transactions on Evolutionary Computation
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A vast number of meta-heuristic algorithms, and their hybridizations, have been presented to solve optimization problems. ...
The objective for a solution methodology that is independent of the problem domain, serves as one of the main motivations for designing hyper-heuristic approaches [6] , [18] . ...
doi:10.1109/tevc.2013.2281527
fatcat:py4cbideknd2nkjhitmrmhd66u
Methods and Applications
[chapter]
1997
After the Event
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a perturbation phase to get out of the corresponding valley. ...
Abstract Variable neighborhood search (VNS) is a metaheuristic, or framework for building heuristics, based upon systematic change of neighborhoods both in a decent phase to find a local minimum, and in ...
Cote et al. [2005] use a simplified Variable Neighborhood Descent in a hybrid multi-objective evolutionary algorithm for the uncapacitated exam proximity problem. ...
doi:10.1016/b978-008043074-4/50023-5
fatcat:7clkbkmqtbgkjdpzgzpjl7ug5e
Variable neighbourhood search: methods and applications
2008
4OR
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It consists of steps for developing a heuristic for any particular problem. Those steps are common to the implementation of other metaheuristics. ...
Variable neighbourhood search (VNS) is a metaheuristic, or a framework for building heuristics, based upon systematic changes of neighbourhoods both in descent phase, to find a local minimum, and in perturbation ...
The third author was partly supported by project TIN2005-08404-C04-03 of the Spanish Government (with financial support from the E.U. under the FEDER project) and project PI042005/044 of the Canary Government ...
doi:10.1007/s10288-008-0089-1
fatcat:3iqvqsdfdra6fn6v3ne5rv2f64
A hybrid MOEA for the capacitated exam proximity problem
Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753)
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A hybrid MOEA is used to solve a bi-objective version of the capacitated exam proximity problem. In this MOEA, the traditional genetic crossover is replaced by two local search operators. ...
The hybrid MOEA was able to produce the lowest proximity cost for two datasets and the second lowest cost for the remaining four datasets. ...
INTRODUCTION This paper presents a hybrid multi-objective evolutionary algorithm designed for the capacitated exam proximity problem. ...
doi:10.1109/cec.2004.1331073
dblp:conf/cec/WongCS04
fatcat:jju66bxevzaw3gv5slpd37bwve
The Vessel Schedule Recovery Problem (VSRP) – A MIP model for handling disruptions in liner shipping
2013
European Journal of Operational Research
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The problem is framed as a multi-indicator assessment and is solved using a minimal cost objective. ...
Multi-objective (MO) route selection problem is a combination of two combinatorial problems: MO shortest path problem (finding the efficient paths between the nodes to be visited) and MO traveling salesperson ...
-Optimal Dynamic Tax Evasion: A Portfolio Approach Francesco Menoncin, Economics, Brescia University, Via S. Faustino, 74/B, 25122, Brescia, Italy, menoncin@eco.unibs.it, Rosella Levaggi ...
doi:10.1016/j.ejor.2012.08.016
fatcat:c27kagfnxnhjfbil2rydhjhomm
Local Organizing Committees
2006
2006 13th IEEE International Conference on Electronics, Circuits and Systems
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Models considering other logistic decisions and its relations with economic parameters could be a good research field. ...
New research could be developed in this area, expanding the limits of the paper that deals with one specific operation and with one specific decision. ...
In order to approach a problem of multi -criteria analysis, it is necessary to establish the following: the objective condition states in which the problem integrates in specific algorithms, the decisional ...
doi:10.1109/icecs.2006.379662
fatcat:556xl3dm5vdfpodzwjmf5qqu6m
Local Organizing Committees
2008
Artificial Organs
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is application/pdf.
Models considering other logistic decisions and its relations with economic parameters could be a good research field. ...
New research could be developed in this area, expanding the limits of the paper that deals with one specific operation and with one specific decision. ...
In order to approach a problem of multi -criteria analysis, it is necessary to establish the following: the objective condition states in which the problem integrates in specific algorithms, the decisional ...
doi:10.1111/j.1525-1594.1989.tb01538.x
fatcat:w67547wxlvbfjlnramoglkz6ba
Local Organizing Committees
[chapter]
2005
Proceedings of the Twentieth International Cryogenic Engineering Conference (ICEC20)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2014; you can also visit the original URL.
The file type is application/pdf.
Models considering other logistic decisions and its relations with economic parameters could be a good research field. ...
New research could be developed in this area, expanding the limits of the paper that deals with one specific operation and with one specific decision. ...
In order to approach a problem of multi -criteria analysis, it is necessary to establish the following: the objective condition states in which the problem integrates in specific algorithms, the decisional ...
doi:10.1016/b978-008044559-5/50002-8
fatcat:hgtll22pt5duvguzik5qx6fxwm
The role of optimal selection of facilities in a supply chain network
2018
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Such viewpoints encompass simple but effective methods (Weighted Factor Rating Method, Load Distance technique), a process that can be adjusted to multi-criteria problems (Analytic Hierarchy Process) as ...
In the solution approach of the specific problem, different viewpoints are used. ...
Diamadidis Alexandros of the Department of Economics at Aristotle University of Thessaloniki. ...
doi:10.26262/heal.auth.ir.300540
fatcat:opijqbb66zewxjcbd5cgaavcu4