A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy
Proceedings of the 3rd International Conference on Genetic Algorithms
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
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In every system, where the resources to be allocated to a given set of tasks are limited, one is faced with scheduling problems, that heavily constrain the enterprise's productivity. The scheduling tasks are typically very complex, and although there has been a growing flow of work in the area, the solutions are not yet at the desired level of quality and efficiency. The Genetic and Evolutionary Algorithms (GEAs) offer, in this scenario, a promising approach to problem solving, considering the good results obtained so far in complex combinatorial optimization problems. The goal of this work is, therefore, to apply GEAs to the scheduling processes, giving a special atten tion to indirect represen tations of the data. One will consider the case of the Job Shop Scheduling Problem, the most challenging and common in industrial environments. A specific application, developed for a Small and Medium Enterprise, the Tipografia Tadinense, Lda, will be presented.