A Parallel Variable Neighborhood Search for Solving Real-World Production-Scheduling Problems

2021 ◽  
pp. 12-20
Author(s):  
Eneko Osaba ◽  
Erlantz Loizaga ◽  
Xabier Goenaga ◽  
Valentin Sanchez
Keyword(s):  
Real World ◽  
Production Scheduling ◽  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
World Production ◽  
Scheduling Problems

scholarly journals Production Scheduling and Customer Orders Assignment in a Three-Level Supply Chain

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
F. Sadeghi Naieni Fard ◽  
B. Naderi ◽  
A. A. Akbari
Keyword(s):  
Production Scheduling ◽  
Variable Neighborhood Search ◽  
Programming Model ◽  
Search Algorithm ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Distribution Centers ◽  
Proposed Model ◽  
Production Distribution ◽  
Neighborhood Search Algorithm

In the classical production-distribution centers problem, only assignment of customers, distribution centers, and suppliers is determined. This paper extends the problem of production-distribution centers assignment by considering sequencing decisions in the supply network. Nowadays, meeting delivery time of products is a competitive benefit; therefore, the objective is to minimize total tardiness. This problem is mathematically formulated by a mixed integer programming model. Then, using the proposed model, small instances of the problem can be optimally solved by GAMS software. Moreover, two metaheuristics based on variable neighborhood search and simulated annealing are proposed to solve large instances of the problem. Finally, performance of the proposed metaheuristics is evaluated by two sets of balanced and unbalanced instances. The computational results show the superiority of the variable neighborhood search algorithm.

scholarly journals A PSO-Based Hybrid Metaheuristic for Permutation Flowshop Scheduling Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Le Zhang ◽  
Jinnan Wu
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Local Optimum ◽  
Scheduling Problems ◽  
Flowshop Scheduling ◽  
Stochastic Variable ◽  
Permutation Flowshop ◽  
Hybrid Metaheuristic ◽  
Benchmark Instances ◽  
Flowshop Scheduling Problem

This paper investigates the permutation flowshop scheduling problem (PFSP) with the objectives of minimizing the makespan and the total flowtime and proposes a hybrid metaheuristic based on the particle swarm optimization (PSO). To enhance the exploration ability of the hybrid metaheuristic, a simulated annealing hybrid with a stochastic variable neighborhood search is incorporated. To improve the search diversification of the hybrid metaheuristic, a solution replacement strategy based on the pathrelinking is presented to replace the particles that have been trapped in local optimum. Computational results on benchmark instances show that the proposed PSO-based hybrid metaheuristic is competitive with other powerful metaheuristics in the literature.

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