Research on Open Shop Scheduling Based on Genetic Algorithm

TL;DR: A mixed integer programming model was established with the objective to minimize the makespan based on the characteristics of the open shop, and a evolution genetic algorithm (EGA) was proposed, and particular crossover operation was proposed which generated multiple offspring at a time.

Abstract: Open shop scheduling problem is a typical NP problem with wide engineering background. It is of importance with respect of theory and application. In this paper, a mixed integer programming model was established with the objective to minimize the makespan based on the characteristics of the open shop, and a evolution genetic algorithm(EGA) was proposed. The representation of chromosome used in this paper was composed of two layers: operation layer and machine layer, which can be encoded and decoded easily. In generating initial population, DS/LTRP heuristic was used in order to improve the quality of the population. And particular crossover operation was proposed, which generated multiple offspring at a time, so that the efficiency of the algorithm can be well improved. At last, the proposed algorithm was tested on taillard benchmark, and numerical example showed good result.