scholarly journals Variable Neighborhood Search Algorithms for an Integrated Manufacturing and Batch Delivery Scheduling Minimizing Total Tardiness

2019 ◽  
Vol 9 (21) ◽  
pp. 4702
Author(s):  
Cheol Min Joo ◽  
Byung Soo Kim
Keyword(s):  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Search Algorithms ◽  
Mixed Integer ◽  
Neighborhood Search ◽  
Manufacturing Plant ◽  
Selection Probability ◽  
Case Selection ◽  
Neighborhood Search Algorithms ◽  
Neighborhood Search Algorithm

This article addresses an integrated problem of one batching and two scheduling decisions between a manufacturing plant and multi-delivery sites. In this problem, two scheduling problems and one batching problem must be simultaneously determined. In the manufacturing plant, jobs ordered by multiple customers are first manufactured by one of the machines in the plant. They are grouped to the same delivery place and delivered to the corresponding customers using a set of delivery trucks within a limited capacity. For the optimal solution, a mixed integer linear programming model is developed and two variable neighborhood search algorithms employing different probabilistic schemes. We tested the proposed algorithms to compare the performance and conclude that the variable neighborhood search algorithm with dynamic case selection probability finds better solutions in reasonable computing times compared with the variable neighborhood search algorithm with static case selection probability and genetic algorithms based on the test results.

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.

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

scholarly journals Two meta-heuristics for solving the multi-vehicle multi-covering tour problem with a constraint on the number of vertices

2020 ◽  
pp. 14-14
Author(s):  
Manel Kammoun ◽  
Houda Derbel ◽  
Bassem Jarboui
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Variable Neighborhood Search ◽  
Search Algorithm ◽  
Descent Method ◽  
Computational Experiments ◽  
Neighborhood Search ◽  
Variable Neighborhood Descent ◽  
Covering Tour Problem ◽  
Neighborhood Search Algorithm

In this work we deal with a generalized variant of the multi-vehicle covering tour problem (m-CTP). The m-CTP consists of minimizing the total routing cost and satisfying the entire demand of all customers, without the restriction of visiting them all, so that each customer not included in any route is covered. In the m-CTP, only a subset of customers is visited to fulfill the total demand, but a restriction is put on the length of each route and the number of vertices that it contains. This paper tackles a generalized variant of the m-CTP, called the multi-vehicle multi-covering Tour Problem (mm-CTP), where a vertex must be covered several times instead of once. We study a particular case of the mm-CTP considering only the restriction on the number of vertices in each route and relaxing the constraint on the length (mm-CTP-p). A hybrid metaheuristic is developet by combining Genetic Algorithm (GA), Variable Neighborhood Descent method (VND), and a General Variable Neighborhood Search algorithm (GVNS) to solve the problem. Computational experiments show that our approaches are competitive with the Evolutionary Local Search (ELS) and Genetic Algorithm (GA), the methods proposed in the literature.

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