A Survey on Variable Neighborhood Search Methods for Supply Network Inventory

2020 ◽  
pp. 71-82
Author(s):  
Angelo Sifaleras ◽  
Ioannis Konstantaras
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Supply Network ◽  
Search Methods

scholarly journals ADAPTATION OF THE VARIABLE NEIGHBORHOOD SEARCH HEURISTIC TO SOLVE THE VEHICLE ROUTING PROBLEM

2012 ◽  
Vol 12 (1) ◽  
pp. 10 ◽  
Author(s):  
ARIF IMRAN ◽  
LIANE OKDINAWATI
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Variable Neighborhood Search ◽  
Initial Solution ◽  
Neighborhood Search ◽  
Search Methods ◽  
Routing Problem ◽  
Search Heuristic ◽  
Dijkstra's Algorithm ◽  
Sweep Algorithm

The vehicle routing problem is investigated by using some adaptations of the variable neighborhood search (VNS).The initial solution was obtained by Dijkstra’s algorithm based on cost network constructed by the sweep algorithm andthe 2-opt. Our VNS algorithm use several neighborhoods which were adapted for this problem. In addition, a number oflocal search methods together with a diversification procedure were used. The algorithm was then tested on the data setsfrom the literature and it produced competitive results if compared to the solutions published.

scholarly journals Enhanced Variable Neighborhood Search-Based Recovery Supplier Selection for Post-Disruption Supply Networks

Processes ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 670
Author(s):  
Yuting Chen ◽  
Ping Lou ◽  
Wen Jiang
Keyword(s):  
Supplier Selection ◽  
Large Scale ◽  
Network Performance ◽  
Variable Neighborhood Search ◽  
Performance Metrics ◽  
Recovery Process ◽  
Neighborhood Search ◽  
Supply Network ◽  
Supply Networks ◽  
Selection Of

With the increasing reliance on global sourcing and the growth in the likelihood of disruptive incidents, today’s supply networks are more prone to unexpected natural and man-made disruptive events. In order to alleviate the losses caused by these disruptive events, when a large-scale event disrupts multiple suppliers simultaneously, a single or several critical suppliers should be selected from the disrupted ones to assist them to recover their production as soon as possible. The selection of these recovery suppliers is of great importance in the recovery process of the entire supply network. Thus, this paper proposes a recovery supplier selection method from the view of the supply network structure. Firstly, a tripartite graph-based supply model is proposed to depict a two-stage supply network, which consists of multiple manufacturers and suppliers as well as the diverse product supply-demand interdependence connecting them. To measure the impacts caused by supplier disruptions and to evaluate the effectiveness of recovery supplier decisions, two supply network performance metrics reflecting product supply availability are also given. Then, the recovery supplier selection problem is described as a combinatorial optimization problem. To solve this problem, a heuristic algorithm, with enhanced variable neighborhood search (EVNS) is designed based on the general framework of a variable neighborhood search. Finally, experiments based on a real-world supply network are conducted. The experimental results indicate that the proposed method is applicable and effective.

Special issue on Variable neighborhood search methods in business and engineering

2017 ◽  
Vol 78 ◽  
pp. 382-384 ◽  
Author(s):  
Abraham Duarte ◽  
Nenad Mladenovic ◽  
Bassem Jarboui
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Special Issue ◽  
Search Methods

scholarly journals Adaptive Variable Neighborhood Search-Based Supply Network Reconfiguration for Robustness Enhancement

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Ping Lou ◽  
Yuting Chen ◽  
Song Gao
Keyword(s):  
Structural Design ◽  
Variable Neighborhood Search ◽  
Real Life ◽  
Tohoku Earthquake ◽  
Neighborhood Search ◽  
Network Reconfiguration ◽  
Supply Network ◽  
Supply Networks ◽  
Robustness Metrics

Robustness of a supply network highly depends on its structure. Although structural design methods have been proposed to create supply networks with optimal robustness, a real-life supply network can be quite different from these optimal structural designs. Meanwhile, real cases such as Thailand floods and Tohoku earthquake demonstrate the vulnerability of supply networks in real life. Obviously, it is urgent to enhance the robustness of existing real-life supply networks. Thus, in this paper, a supply network reconfiguration method based on adaptive variable neighborhood search (AVNS) is proposed to enhance the structural robustness of supply networks facing both random and target disruptions. Firstly, a supply network model considering the heterogeneous roles of entities is introduced. Based on the model, two robustness metrics, Rr and Rt, are proposed to describe the tolerance of supply networks facing random and target disruptions, respectively. Then, the problem of reconfiguration-based supply network robustness enhancement is described. To solve the problem effectively and efficiently, a new heuristic based on general variable neighborhood search, namely, AVNS, is proposed. Finally, a case study based on three real-life supply networks is presented to verify the applicability and effectiveness of the proposed robustness enhancing method.

Variable Neighborhood Search Methods

2008 ◽  
pp. 3975-3989 ◽  
Author(s):  
Pierre Hansen ◽  
Nenad Mladenović
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Search Methods
Sign in / Sign up

Export Citation Format

Share Document