A Hybrid Algorithm for Scheduling of Dual-Resource Constrained Job Shop

This paper presents a hybrid algorithm, based on ant colony algorithm, developed to address the dual-resource constrained job shop scheduling problem with heterogeneous workers. The algorithm establishes a dynamic candidate solution set, based on the technology constraint, for each ant to improve the calculating efficiency of the algorithm. Meanwhile, the algorithm utilizes the simulated annealing algorithm as the local search mechanism to improve the quality of optimum solution. A study is conducted, using the proposed scheduling method, to compare the performance of four dispatching rules for machine and worker assignment to jobs. With the optimal resource collocating strategy, then the proposed algorithm is compared with another ant colony algorithm on considerable random examples. The results indicate that more optimal scheduling schemes are obtained with the hybrid ant colony algorithm in most cases.