Inter-Machine JOXに基づくJSPの進化的解法

抄録

In this paper, we propose a new genetic algorithm(GA) for job-shop scheduling problems(JSPs), considering dependencies among machines. We regard the crossover as a main search operator. Crossovers should preserve characteristics between parents and their children in order for GAs to perform well. Characteristics are elements that constitute a solution and determine the fitness of the solution. Chracteristics also should be highly independent of each other. A characteristic has to be found for each problem domain since it depends on a particular problem domain. We basically regard the processing order of jobs as a characteristic for JSPs. We consider job-based order inheritance and position-based order inheritance for ways of inheritance of the processing order by crossovers, and propose two new crossovers; the Inter-machine Job-based Order Crossover(Inter-machine JOX) and the Inter-machine Position-based Order Crossover(Inter-machine POX). By applying them to the benchmark problems of FT10×10 and FT20×5, we demonstrate that the Inter-machine JOX shows better performance than the Inter-machine POX and an existing crossover, the SXX[Kobayashi 95]. The Inter-machine JOX preserves both the processing order of jobs and the technological ordering which causes dependencies among machines. We also propose a new mutation named the Inter-machine Job-based Shift Change for introducing a diversity of population. We confirm its effectiveness by applying it with the Inter-machine JOX to FT10×10 and FT20×5.