Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Journal of Computational and Applied Mathematics - Special issue in honor of Professor Dr. F. Broeckx
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy
Evolutionary Computation
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Order acceptance using genetic algorithms
Computers and Operations Research
Research of multi-population agent genetic algorithm for feature selection
Expert Systems with Applications: An International Journal
Using a greedy random adaptative search procedure to solve the cover printing problem
Computers and Operations Research
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
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Inspired by successful application of evolutionary algorithms to solving difficult optimization problems, we explore in this paper, the applicability of genetic algorithms (GAs) to the cover printing problem, which consists in the grouping of book covers on offset plates in order to minimize the total production cost. We combine GAs with a linear programming solver and we propose some innovative features such as the ''unfixed two-point crossover operator'' and the ''binary stochastic sampling with replacement'' for selection. Two approaches are proposed: an adapted genetic algorithm and a multiobjective genetic algorithm using the Pareto fitness genetic algorithm. The resulting solutions are compared. Some computational experiments have also been done to analyze the effects of different genetic operators on both algorithms.