Job Shop Scheduling has many applications in real production systems such as metal machining, printing, and textiles, among others. Commonly, in these manufacturing systems the main objective is the delivery of the jobs on time. In this research we present a hybrid approach that uses the Shifting Bottleneck (SB) and Tabu Search (TS) heuristics with the purpose of minimizing the Total Weighted Tardiness. The Shifting Bottleneck algorithm provides a feasible initial solution which is iteratively improved by the TS method. Additionally, several improvements were performed on the classical algorithms SB and TS such as new criteria for the selection of the critical machines and a number of innovative strategies of diversification and intensification. The performance of the proposed heuristic algorithm denominated CBBT was evaluated with 17 classical problems found in the literature. The implemented heuristic algorithm shows very competitive results compared with other approaches found in literature both in quality of the solutions and computational time.
sistemas flexibles de manufactura, programación de la producción, algoritmosFlexible manufacturing systems, production scheduling, algorithms
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