Sequencing with earliness and tardiness penalties: a review
Operations Research
Computers and Operations Research
Computers and Industrial Engineering
Using tabu search to solve the common due date early/tardy machine scheduling problem
Computers and Operations Research
Computers and Operations Research
Benchmarks for scheduling on a single machine against restrictive and unrestrictive common due dates
Computers and Operations Research
Variable neighborhood search for the degree-constrained minimum spanning tree problem
Discrete Applied Mathematics - Special issue: Third ALIO-EURO meeting on applied combinatorial optimization
Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
Design and Analysis of Experiments
Design and Analysis of Experiments
Computers and Industrial Engineering
A differential evolution approach for the common due date early/tardy job scheduling problem
Computers and Operations Research
Computers and Operations Research
Computers and Industrial Engineering
Computers and Operations Research
Expert Systems with Applications: An International Journal
Flexible job-shop scheduling with parallel variable neighborhood search algorithm
Expert Systems with Applications: An International Journal
A hybrid immune simulated annealing algorithm for the job shop scheduling problem
Applied Soft Computing
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
An efficient hybrid algorithm for resource-constrained project scheduling
Information Sciences: an International Journal
Computers and Operations Research
A novel global harmony search algorithm for reliability problems
Computers and Industrial Engineering
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A novel global harmony search algorithm for task assignment problem
Journal of Systems and Software
Harmony filter: A robust visual tracking system using the improved harmony search algorithm
Image and Vision Computing
Information Sciences: an International Journal
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Review Article: Solving 0-1 knapsack problem by a novel global harmony search algorithm
Applied Soft Computing
A hybrid harmony search algorithm for the blocking permutation flow shop scheduling problem
Computers and Industrial Engineering
Information Sciences: an International Journal
A chaotic harmony search algorithm for the flow shop scheduling problem with limited buffers
Applied Soft Computing
Information Sciences: an International Journal
Performance assessment of foraging algorithms vs. evolutionary algorithms
Information Sciences: an International Journal
Computers and Operations Research
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
A harmony search algorithm for nurse rostering problems
Information Sciences: an International Journal
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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.