Hybrid genetic algorithm for coordinated production and transportation planning problem

Abstract

A hybrid genetic algorithm is proposed to solve a coordinated production and transportation problem. The problem considered is a mixed integer linear programming problem, which coordinates the production planning of finished products and intermediate products in a process industry, also consists of transportation between the facilities that produces intermediates and finished products. The results obtained by GA are then compared with results obtained by CPLEX solver. Computational results show that as the problem size increase in terms of number of products or time periods, GA can provide a good quality feasible solution in a reasonable time. Furthermore, incorporating the feasible solution from the MIP solver into GA's initial population decreases the total cost by about 39%.