A Multiobjective Approach to Fuzzy Job Shop Problem Using Genetic Algorithms
Current Topics in Artificial Intelligence
A Study of Schedule Robustness for Job Shop with Uncertainty
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Fast Local Search for Fuzzy Job Shop Scheduling
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Improving local search for the fuzzy job shop using a lower bound
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Particle swarm optimisation for open shop problems with fuzzy durations
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Swarm-based neighbourhood search for fuzzy job shop scheduling
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Combining neighbourhoods in fuzzy job shop problems
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In the sequel, we consider the fuzzy job-shop problem, which is a variation of the job-shop problem where duration of tasks may be uncertain and where due-date constraints are allowed to be flexible. Uncertain durations are modeled using triangular fuzzy numbers, and due-date constraints are fuzzy sets with decreasing membership functions expressing a flexible threshold ldquoless than.rdquo Also, the objective function is built using fuzzy decision-making theory. We propose the use of a genetic algorithm (GA) to find solutions to this problem. Our aim is to provide a semantics for this type of problems and use this semantics in a methodology to analyze, evaluate, and, therefore, compare solutions. Finally, we present the results obtained using the GA and evaluate them using the proposed methodology.