Bi-Gender genetic algorithm to solve production and transportation scheduling in multi-site manufacturing system

Today, the use of multi-site manufacturing systems has attracted the attention of many factories due to its benefits, such as reduced transportation costs, concentration of population, pollution, facilities and traffic in one area, and improved service to customers. This paper addresses the problem of scheduling a distributed flexible job-shop scheduling problem with two objective functions of minimizing the total delivery times of orders and the total production and transportation costs. In this case, it is assumed that there are several manufacturing units in different geographic regions, each of which has a flexible job-shop environment. The purpose of this paper is to determine how to allocate orders to manufacturing units, assign operations to machines of the related manufacturing unit, and determine sequence of processing of the assigned operations to a machine for minimizing the total delivery times of orders and the total production and transportation costs. Since the problem has NP-Hard complexity, meta-heuristic algorithms should be used solve it. In this paper, a genetic algorithm is proposed to solve the problem called a Bi-Gender genetic algorithm with two sets of chromosomes. The first group of chromosomes is male and the second group of chromosomes is female. In order to perform a crossover operator, one parent should be selected from the first category and the second one from the second category. Comparing the results of this algorithm with the development of a genetic algorithm in the subject literature indicates the high efficiency of the proposed algorithm.