Fuzzy sets, decision making and expert systems
Fuzzy sets, decision making and expert systems
On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
A tutorial survey of job-shop scheduling problems using genetic algorithms—I: representation
Computers and Industrial Engineering
Genetic Algorithms and Fuzzy Multiobjective Optimization
Genetic Algorithms and Fuzzy Multiobjective Optimization
Ant Colony Optimization
How to Solve It: Modern Heuristics
How to Solve It: Modern Heuristics
A fuzzy genetic algorithm for real-world job shop scheduling
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
Soft computing optimization methods applied to logistic processes
International Journal of Approximate Reasoning
Conflict, harmony, and independence: relationships in evolutionary multi-criterion optimisation
EMO'03 Proceedings of the 2nd international conference on Evolutionary multi-criterion optimization
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Optimizing logistic processes using a fuzzy decision making approach
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Rescheduling and optimization of logistic processes using GA and ACO
Engineering Applications of Artificial Intelligence
Information Sciences: an International Journal
Information Sciences: an International Journal
Review article: A review of soft computing applications in supply chain management
Applied Soft Computing
Some concepts of the fuzzy multicommodity flow problem and their application in fuzzy network design
Mathematical and Computer Modelling: An International Journal
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Logistic scheduling problems are often multi-criteria optimization problems, with many contradictory objectives and constraints, which cannot be properly described by conventional cost functions. The use of fuzzy decision making may improve the performance of this type of systems, since it allows an easier and suitable description of the confluence of the different criteria of the scheduling process. This paper introduces the application of fuzzy weighted aggregation to formulate the logistic system optimization problem. Further, this paper also extends the application of this framework to different types of optimization methodologies: dispatching rules, if it is used as a performance index; or meta-heuristics, such as genetic algorithms (GA) or ant colony optimization (ACO), if it is used as an objective function. Simulation results show that the fuzzy combination of criteria improves the scheduling results whatever optimization methodology is used.