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
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms
A fast algorithm for assortment optimization problems
Computers and Operations Research
Genetic Algorithms for the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
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Assortment problems arise in various industries such as the steel, paper, textiles and transportation industries. Two-dimensional assortment problems involve finding the best way of placing a set of rectangles within another rectangle whose area is minimized. Such problems are nonlinear and combinatorial. Current mixed integer programming models give optimal solutions, but the computation times are unacceptable. This study proposes a genetic algorithm that incorporates a novel random packing process and an encoding scheme for solving the assortment problem. Numerical examples indicate that the proposed genetic algorithm is considerably more efficient and effective than a fast integer programming model. Errors with respect to the optimal solutions are low such that numerous practical industrial cutting problems can be solved efficiently using the proposed method.