Lot streaming and scheduling heuristics for m-machine no-wait flowshops
Computers and Industrial Engineering
Minimizing the mean weighted absolute deviation from due dates in lot-streaming flow shop scheduling
Computers and Operations Research
A discrete version of particle swarm optimization for flowshop scheduling problems
Computers and Operations Research
Evolutionary algorithms for scheduling m-machine flow shop with lot streaming
Robotics and Computer-Integrated Manufacturing
An effective hybrid PSO-based algorithm for flow shop scheduling with limited buffers
Computers and Operations Research
Flow shop scheduling with lot streaming
Operations Research Letters
An Intelligent Tuned Harmony Search algorithm for optimisation
Information Sciences: an International Journal
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Circle Detection by Harmony Search Optimization
Journal of Intelligent and Robotic Systems
A hybrid harmony search algorithm for the spread spectrum radar polyphase codes design problem
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
Discrete harmony search algorithm for dynamic FJSSP in remanufacturing engineering
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Hybrid discrete harmony search algorithm for scheduling re-processing problem in remanufacturing
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Survey A survey on applications of the harmony search algorithm
Engineering Applications of Artificial Intelligence
Hybrid parallel chaos optimization algorithm with harmony search algorithm
Applied Soft Computing
Hi-index | 12.05 |
In this paper, a local-best harmony search (HS) algorithm with dynamic sub-harmony memories (HM), namely DLHS algorithm, is proposed to minimize the total weighted earliness and tardiness penalties for a lot-streaming flow shop scheduling problem with equal-size sub-lots. First of all, to make the HS algorithm suitable for solving the problem considered, a rank-of-value (ROV) rule is applied to convert the continuous harmony vectors to discrete job sequences, and a net benefit of movement (NBM) heuristic is utilized to yield the optimal sub-lot allocations for the obtained job sequences. Secondly, an efficient initialization scheme based on the NEH variants is presented to construct an initial HM with certain quality and diversity. Thirdly, during the evolution process, the HM is dynamically divided into many small-sized sub-HMs which evolve independently so as to balance the fast convergence and large diversity. Fourthly, a new improvisation scheme is developed to well inherit good structures from the local-best harmony vector in the sub-HM. Meanwhile, a chaotic sequence to produce decision variables for harmony vectors and a mutation scheme are utilized to enhance the diversity of the HM. In addition, a simple but effective local search approach is presented and embedded in the DLHS algorithm to enhance the local searching ability. Computational experiments and comparisons show that the proposed DLHS algorithm generates better or competitive results than the existing hybrid genetic algorithm (HGA) and hybrid discrete particle swarm optimization (HDPSO) for the lot-streaming flow shop scheduling problem with total weighted earliness and tardiness criterion.