Decentralized Tabu Searches in Multi Agent System for Distributed and Flexible Job Shop Scheduling Problem

Abstract

Scheduling in production systems consists in assigning operations on a set of available resources in order to achieve defined objectives. The Flexible Job shop Scheduling Problem (FJSP) is one of the scheduling problems where each operation can be processed on different machine and its processing time depends on the used machine. But in the recent years, many companies decide to move towards the decentralization of their factories which allow it to gain advantages towards its customers. In the case of the classic Flexible Job shop Scheduling Problem, we assume that there is a single factory with a set of m machines and n jobs, but in Distributed and Flexible Job shop Scheduling Problem (DFJSP), there is a set of geographically distributed factories in different locations. Each factory contains m machines on which n jobs must be processed. The Distributed scheduling problems and more specifically the DFJSP are much more complicated than standard problems because they involve not only the problem of assigning jobs to machines but also the problem of distribution of jobs in different factories. So, the DFJSP is harder than the FJSP. The DFJSP is classified, as most of scheduling problems, NP-Hard in complexity theory. In this paper, we propose a decentralized model based on tabu search to solve the Distributed and Flexible Job shop Scheduling Problem in order to minimize the maximum completion time (makespan). To evaluate the performance of our model, a set of experiments are performed on benchmark instances well known in the literature.