Research On Two-objective JSSP Based On Double-population Genetic Algorithm

Shop scheduling has always been the core activities of production management,job shop scheduling problem is simplified in many practical scheduling model. In recent years, various intelligent algorithms gradually introduced to scheduling problems, Genetic algorithm is the most widely used method of optimization, it is not dependent on the characteristics of the problem, implicit parallelism, etc,but its easy to premature convergence. Double-population genetic algorithm can overcome the shortage of genetic algorithm, more suitable for complex optimization problems, compared with other optimization techniques it has significant advantage, its application scope become more and more widely.In this paper, on the basis of the research on job shop scheduling problem at home and abroad, first to do a classification on the job shop problem,then narrative the course of development of job shop scheduling problem method for solving, summary the existing research results and analysis research trends of job shop scheduling problem from the development of scheduling algorithm and the development of object of scheduling. Then introduced the job-shop scheduling algorithm theoretical basis, including the basic theory of genetic algorithm, douple population genetic algorithm and the basic theory of adaptive genetic algorithm. On this basis, further studies carried out. First of all, taking into account the importance of product make span and product delays in the many objectives of the of scheduling, established with minimum make span time and minimum delay time mathematical model of two-objective job shop scheduling problem. And then to solve the double-goal job shop scheduling model, then design double-population genetic algorithm the solvetion of this model in detail; including:encoding and decoding method based on process, the choice of fitness function, select operation, crossover operation, mutation, and design the operating parameters of algorithm. Finally, a numerical example carried out, programming to solve job shop scheduling problem of a standard example FT06and a complex practical example using designed double-population genetic algorithm, the result show the designed double-population algorithm can not only solve the problem but better than the standard genetic algorithm to solve the problem. In this paper, established with minimum make span time and minimum delay time mathematical model of two-objective job shop scheduling problem, and designed two-population genetic algorithm to solve the model, results show that two-population genetic algorithm can solve the dual objectives of job shop scheduling problem..