A HYBRID PARTICLE SWARM OPTIMIZATION AND VARIABLE NEIGHBORHOOD SEARCH TO SOLVE THE PRODUCTION ON ORDERS PROBLEM

Today, the problems of the enterprises revolve essentially around the multi-objectives problems that can be divided into several sub-problems and solved by the combination of several resolution tools. In this paper, we describe and formulate the production on orders problem using the goal programming model. The production on orders problem is a multi-objective problem which consists to make a compromise between the inside (benet) and the outside (tardiness and rupture) of the society. We develop two versions of Hybrid Particle Swarm Optimization (gbest PSO and proposed PSO) and Variable Neighbourhood Search to solve the formulated model. We apply the developed algorithm to solve some instances. The experimental results show that the proposed PSO is more ecient than the gbest PSO to converge towards the optimal solution.