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In most production environment, there is a requirement for effective use of the available resources. Job Shop Scheduling Problem (JSSP) because of its key impact on revenues is at the crux of production planning, of late also known as Enterprise Resource Planning (ERP). Industrial tasks ranging from assembling cars to scheduling airplane maintenance crews are easily modeled as instances of JSSP, and improving solutions by even as little as one percent can have a significant financial impact. Efforts have been put to find not necessarily an optimal solution, but a good one to solve these problems. Tabu Search (TS) is an effective local search algorithm for the JSSP, but the quality of the best solution found depends on the initial solution used. The motivation behind such a paper is to layout critical discussion on the Tabu Search technique for JSSP, based on neighborhood structures for finding initial solutions, in order to better serve the needs of manufacturing community trying to apply Tabu Search technique on their problems. In this paper a approach is presented that uses a different methods, that either single scheduling or double scheduling, with functions of neighborhood selection in Tabu Search Method. The approach is tested on a set of standards instances taken from the literature and compared with other approaches. The computation results validate some effectiveness of the proposed algorithm.

META-HEURISTIC PROCEDURE TO FIND THE SOLUTION OF JOB SHOP SCEDULING PROBLEM