A Multi-objective Variable Neighborhood Search algorithm for solving the Hybrid Flow Shop Problem

2018 ◽  
Vol 66 ◽  
pp. 87-94 ◽  
Author(s):  
E.C. de Siqueira ◽  
M.J.F. Souza ◽  
S.R. de Souza
Keyword(s):  
Variable Neighborhood Search ◽  
Flow Shop ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Hybrid Flow Shop ◽  
Multi Objective ◽  
Flow Shop Problem ◽  
Objective Variable ◽  
Neighborhood Search Algorithm

scholarly journals Using Non-dominated Sorting Particle Swarm Optimization Algorithm II for Bi-objective Flow Shop Scheduling Problems

2021 ◽  
pp. 275-288
Author(s):  
Hanan Ali Chachan ◽  
Faez Hassan Ali
Keyword(s):  
Hybrid Algorithm ◽  
Variable Neighborhood Search ◽  
Flow Shop ◽  
Search Algorithm ◽  
Flow Shop Scheduling ◽  
Neighborhood Search ◽  
Pareto Solution ◽  
Swarm Optimization ◽  
Shop Scheduling ◽  
Neighborhood Search Algorithm

A hybrid particulate swarm optimization (hybrid) combination of an optimization algorithm of the particle swarm and a variable neighborhood search algorithm is proposed for the multi-objective permutation flow shop scheduling problem (PFSP) with the smallest cumulative completion time and the smallest total flow time. Algorithm for hybrid particulate swarm optimization (HPSO) is applied to maintain a fair combination of centralized search with decentralized search. The Nawaz-Enscore-Ham )NEH) heuristic algorithm in this hybrid algorithm is used to initialize populations in order to improve the efficiency of the initial solution. The method design is based on ascending order (ranked-order-value, ROV), applying the continuous PSO algorithm to the PFSP, introducing the external archive set storage Pareto solution, and using a hybrid strategy that combines strong dominance and aggregation distance to ensure the distribution of the solution set. We adopted the Sigma method and the roulette method, based on the aggregation distance, to select the global optimal solution. A variable neighborhood search algorithm was proposed to further search the Pareto solution in the external set. The suggested hybrid algorithm was used to solve the Taillard test set and equate the test results with the SPEA2 algorithm to check the scheduling algorithm’s efficacy.

scholarly journals A hybrid variable neighborhood search algorithm for solving multi-objective flexible job shop problems

2010 ◽  
Vol 7 (4) ◽  
pp. 907-930 ◽  
Author(s):  
Jun-Qing Li ◽  
Quan-Ke Pan ◽  
Sheng-Xian Xie
Keyword(s):  
Variable Neighborhood Search ◽  
Job Shop ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Flexible Job Shop ◽  
Operation Sequencing ◽  
Hybrid Variable ◽  
Multi Objective ◽  
Machine Assignment ◽  
Neighborhood Search Algorithm

In this paper, we propose a novel hybrid variable neighborhood search algorithm combining with the genetic algorithm (VNS+GA) for solving the multi-objective flexible job shop scheduling problems (FJSPs) to minimize the makespan, the total workload of all machines, and the workload of the busiest machine. Firstly, a mix of two machine assignment rules and two operation sequencing rules are developed to create high quality initial solutions. Secondly, two adaptive mutation rules are used in the hybrid algorithm to produce effective perturbations in machine assignment component. Thirdly, a speed-up local search method based on public critical blocks theory is proposed to produce perturbation in operation sequencing component. Simulation results based on the well-known benchmarks and statistical performance comparisons are provided. It is concluded that the proposed VNS+GA algorithm is superior to the three existing algorithms, i.e., AL+CGA algorithm, PSO+SA algorithm and PSO+TS algorithm, in terms of searching quality and efficiency.

scholarly journals A Multi-Objective Variable Neighborhood Search Algorithm for Precast Production Scheduling

2020 ◽  
Vol 24 (6) ◽  
pp. 139-157
Author(s):  
Zong Lehuang ◽  
Wanatchapong Kongkaew
Keyword(s):  
Production Scheduling ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Precast Concrete ◽  
Real Life ◽  
Neighborhood Search ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
Concrete Production ◽  
Objective Variable

In real life, precast production schedulers face the challenges of creating a reasonable schedule to satisfy multiple conflicting objectives. Practical constraints and objectives encountered in the precast production scheduling problem (PPSP) were addressed, with the goal to minimize makespan and total earliness and tardiness penalties. A multi-objective variable neighborhood search (MOVNS) algorithm was proposed and the performance was tested on 11 problem instances. Ten of these were generated using precast concrete production information taken from the literature. One real industrial problem from a precast concrete company was considered as a case study. Extensive experiments were conducted, and the spread and distance metrics were used to evaluate the quality of the non-dominated solutions set. Statistical analysis demonstrated that the result was statistically convincing. Computational results showed that the proposed MOVNS algorithm was significantly better when compared to the other nine algorithms. Therefore, the proposed MOVNS algorithm was a very competitive method for the considered PPSP.

A variable neighborhood search algorithm for optimal protection coordination of power systems

2021 ◽  
Author(s):  
H. R. E. H. Bouchekara ◽  
M. S. Shahriar ◽  
M. S. Javaid ◽  
Y. A. Sha’aban ◽  
M. Zellagui ◽  
...  
Keyword(s):  
Power Systems ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Neighborhood Search ◽  
Neighborhood Search Algorithm ◽  
Optimal Protection
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