Solving a real complex scheduling problem with a Simulation-based optimization method

In this paper, we have studied a complex industrial production problem in the algerian engineering service company - General Electric oil and gaz. The objective of our work is to schedule the most important part of the workshop of Algesco by proposing a coupling between a simulation of the industrial systemand an algorithm of optimization. This new method consists in determining the optimal order of passage of the jobs to be treated in the queue of each machine of the workshop given the large size of the data and the exibility of the model. Two proposed simulation models treat the problem were designed. The first model minimises the completion time of all jobs (Makespan) while the second model minimizes the sum of the delays. A simulation based optimisation algorithm is proposed to solve this problem. It is a combination of the simulation software Flexim and a genetic algorithm. The effectiveness of the approach has been illustrated by numerical experiments on real company data. The results show the efficiency of the proposed method.