A Variable Neighbourhood Search for the Workforce Scheduling and Routing Problem

2015 ◽  
pp. 247-259 ◽  
Author(s):  
Rodrigo Lankaites Pinheiro ◽  
Dario Landa-Silva ◽  
Jason Atkin
Keyword(s):  
Variable Neighbourhood Search ◽  
Workforce Scheduling ◽  
Routing Problem ◽  
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.

A general variable neighbourhood search for the multi-product inventory routing problem

2014 ◽  
Vol 27 (1) ◽  
pp. 39-54 ◽  
Author(s):  
Anis Mjirda ◽  
Bassem Jarboui ◽  
Jelena Mladenović ◽  
Christophe Wilbaut ◽  
Saïd Hanafi
Keyword(s):  
Variable Neighbourhood Search ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Neighbourhood Search ◽  
Product Inventory

scholarly journals Enhancement of Firefly Technique for Effective Optimization of Multi-Depot Vehicle Routing

2019 ◽  
Vol 8 (11) ◽  
pp. 2346-2353 ◽  
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Research Work ◽  
Variable Neighbourhood Search ◽  
Two Phase ◽  
Routing Problem ◽  
Bus Routing ◽  
Pareto Ranking ◽  
Neighbourhood Search

Vehicle Routing Problem (VRP) plays a significant role in today’s demanding world, especially in Logistics, Disaster relief supplies or Emergency transportation, Courier services, ATM cash replenishment, School bus routing and so on and it acts as a central hub for distribution management. The objectives of the present research are to solve NP-Hard Multi-depot Vehicle Routing Problem (MDVRP) by using an enhanced firefly approach as well as to examine the efficiency of the proposed technique Cordeau benchmark dataset of MDVRP were used. The foremost principle of MDVRP is to optimize the cost of the solution, to minimize the overall vehicles, travelling distance and number of routes. MDVRP is constructed with two phase, assignment and routing. The firefly technique is enhanced by using inter depot, which is applied in assignment phase. In routing phase saving cost, intra and inter-route were used. The results were compared with Ant colony optimization (ACO), Genetic algorithm (GA), Intelligent water drops (IWD), Particle Swarm Optimization (PSO), Genetic cluster (GC), Genetic using Pareto Ranking (GAPR), Nomadic Genetic algorithm (NGA), and General Variable neighbourhood search (GVNS) algorithm. The solutions obtained in this research work found to be optimal for most of the benchmark instances

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