Hybridization of harmony search with variable neighborhood search for restrictive single-machine earliness/tardiness problem

Earliness/tardiness scheduling, in connection with Just-In-Time manufacturing philosophy, is crucial in reducing the production cost while maintaining a high service level. In this article, the well-known restrictive single-machine earliness/tardiness scheduling problem (RSMETP) is addressed. A novel hybrid metaheuristic, named as PHVNS, is developed for this NP-hard problem. There are three main innovative aspects in the proposed PHVNS. First, a permutation-based harmony search (PHS) is developed in compliance with the RSMETP features and optimality properties. Secondly, in order to provide an effective balance between the global diversification and local intensification, an enhanced basic variable neighborhood search (EBVNS) is incorporated into the iterative PHS. Thirdly, several problem-dependent mechanisms are introduced to facilitate the search process of PHVNS, such as the distinctive schedule representation, specific tweaks and speed-ups to the new harmony vector, and local search strategies within a neighborhood. An extensive calibration for the main parameters in PHVNS is carried out with the aid of a carefully designed set of experiments. To evaluate and validate the fine-tuned PHVNS, computational experiments are conducted upon the test suite of 280 benchmark instances. As demonstrated in the results, the tuned PHVNS is capable of reaching the high-quality solutions in reasonable time for most of the instances. Compared with some state-of-the-art metaheuristics for RSMETP, PHVNS shows high competitiveness.