
doi: 10.1111/itor.12109
AbstractThis paper describes a biased random‐key genetic algorithm (BRKGA) for the minimization of the open stacks problem (MOSP). The MOSP arises in a production system scenario, and consists of determining a sequence of cutting patterns that minimize the maximum number of open stacks during the cutting process. The proposed approach combines a BRKGA and a local search procedure for generating the sequence of cutting patterns. A novel fitness function for evaluating the quality of the solutions is also developed. Computational tests are presented using available instances taken from the literature. The high quality of the solutions obtained validate the proposed approach.
random keys, Combinatorial optimization, biased random-key genetic algorithm, minimization of open stacks problem, Approximation methods and heuristics in mathematical programming, cutting pattern
random keys, Combinatorial optimization, biased random-key genetic algorithm, minimization of open stacks problem, Approximation methods and heuristics in mathematical programming, cutting pattern
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