scholarly journals The capacitated single-source p-center problem in the presence of fixed cost and multilevel capacities using VNS and aggregation technique

2018 ◽  
Vol 28 (4) ◽  
pp. 453-473
Author(s):  
Chandra Irawan ◽  
Kusmaningrum Soemadi
Keyword(s):  
Mathematical Model ◽  
Exact Method ◽  
Maximum Distance ◽  
Variable Neighbourhood Search ◽  
Fixed Cost ◽  
Single Source ◽  
Center Problem ◽  
Limited Budget ◽  
Neighbourhood Search ◽  
Aggregation Technique

In this study, the discrete p-center problem with the presence of multilevel capacities and fixed (opening) cost of a facility under a limited budget is investigated. A mathematical model of the problem is produced, where we seek the location of open facilities, their corresponding capacities, and the allocation of the customers to the open facilities in order to minimise the maximum distance between customers and their assigned facilities. Two matheuristic approaches are also proposed to deal with larger instances. The first approach is a hybridisation of a clustering-based technique, an exact method, while the second one is based on Variable Neighbourhood Search (VNS). Computational experiments show that the proposed methods produce interesting and competitive results on newly and randomly generated datasets.

scholarly journals Variable Neighbourhood Search

2003 ◽  
Vol 7 (19) ◽  
Author(s):  
P. Hansen ◽  
N. Mladenovic ◽  
J.A. Moreno
Keyword(s):  
Variable Neighbourhood Search ◽  
Neighbourhood Search

Solving Vehicle Routing Problems Using Constraint Programming and Lagrangean Relaxation in a Metaheuristics Framework

2011 ◽  
Vol 4 (2) ◽  
pp. 61-81 ◽  
Author(s):  
D. Guimarans ◽  
R. Herrero ◽  
J. J. Ramos ◽  
S. Padrón
Keyword(s):  
Vehicle Routing ◽  
Constraint Programming ◽  
Complete Solution ◽  
Lagrangean Relaxation ◽  
Variable Neighbourhood Search ◽  
Relaxation Methods ◽  
Routing Problem ◽  
Neighbourhood Search ◽  
Test Instance ◽  
Initial Feasible Solution

This paper presents a methodology based on the Variable Neighbourhood Search metaheuristic, applied to the Capacitated Vehicle Routing Problem. The presented approach uses Constraint Programming and Lagrangean Relaxation methods in order to improve algorithm’s efficiency. The complete problem is decomposed into two separated subproblems, to which the mentioned techniques are applied to obtain a complete solution. With this decomposition, the methodology provides a quick initial feasible solution which is rapidly improved by metaheuristics’ iterative process. Constraint Programming and Lagrangean Relaxation are also embedded within this structure to ensure constraints satisfaction and to reduce the calculation burden. By means of the proposed methodology, promising results have been obtained. Remarkable results presented in this paper include a new best-known solution for a rarely solved 200-customers test instance, as well as a better alternative solution for another benchmark problem.

scholarly journals Location Decision Making and Transportation Route Planning Considering Fuel Consumption

2019 ◽  
Vol 5 (2) ◽  
pp. 27 ◽  
Author(s):  
Chalermchat Theeraviriya ◽  
Rapeepan Pitakaso ◽  
Kittima Sillapasa ◽  
Sasitorn Kaewman
Keyword(s):  
Fuel Consumption ◽  
Palm Oil ◽  
Processing Time ◽  
Computational Study ◽  
Exact Method ◽  
Neighborhood Search ◽  
Fixed Cost ◽  
Location Routing ◽  
Consumption Cost

This study presents the Location Routing Problem (LRP) for which we have created a model for the integration of locating facilities and vehicle routing decisions to solve the problem. The case study is the Palm Oil Collection Center, which is also important for the supply chain system. A mathematical model was made to minimize the total cost of a facility-opening cost, fixed cost of vehicle uses and fuel consumption cost. The fuel consumption cost relies on the distance and road conditions, in case of poor physical condition of a road, and its width, which can be affected the speed of the vehicle as well as the used fuel. Thus, we propose an Adaptive Large Neighborhood Search (ALNS) based on heuristic for solving the LRP. The ALNS method was tested with three datasets of samples divided into small, medium and large problems. Then, the results were compared with the results from the exact method by the Lingo program. The computational study indicated that the ALNS algorithm was competitive to the results of the Lingo for all instance sizes. Moreover, the ALNS was more effective than the exact method; approximately 99% in terms of processing time. We extended this approach to solve the case study, which was considered to be the largest problem, and the ALNS algorithm was efficient with acceptable solutions and short processing time. Therefore, the proposed method provided an effective solution to manage location routing decision of the palm oil collection center.

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