scholarly journals Sequential Simulated Annealing for the Vehicle Routing Problem with Time Windows

2009 ◽  
Vol 3 (2) ◽  
pp. 87-100 ◽  
Author(s):  
Marcin Woch ◽  
Piotr Łebkowski
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Simulated Annealing Algorithm ◽  
Optimization Problems ◽  
Time Windows ◽  
High Quality ◽  
Routing Problem ◽  
Annealing Algorithm ◽  
Very High

This article presents a new simulated annealing algorithm that provides very high quality solutions to the vehicle routing problem. The aim of described algorithm is to solve the vehicle routing problem with time windows. The tests were carried out with use of some well known instances of the problem defined by M. Solomon. The empirical evidence indicates that simulated annealing can be successfully applied to bi-criterion optimization problems.

Hybrid Genetic Simulated Annealing Algorithm with its Application in Vehicle Routing Problem with Time Windows

2010 ◽  
Vol 148-149 ◽  
pp. 395-398
Author(s):  
Qiang Zhang ◽  
Qing Guo Lin ◽  
Qin He Zhang ◽  
Ji Chen Fang ◽  
Zhan Gen Wang ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Simulated Annealing Algorithm ◽  
Time Windows ◽  
Routing Problem ◽  
Genetic Simulated Annealing Algorithm ◽  
Annealing Algorithm ◽  
Set Up ◽  
Delayed Time

Under the situations of distribution center and customer demand, a mathematical model of Vehicle Routing Problem with Time Windows(VRPTW) is set up, where the main factors of less total distance of vehicles driving and less delayed time of vehicles are considered. For the "premature" convergence in Genetic Algorithms, Simulated Annealing Algorithm is introduced, and GSA is designed to optimize and analyse the VRPTW examples. It is shown that the performance of GSA is better than Genetic Annealing(GA).

A Hybrid Meta-Heuristic Algorithm for Vehicle Routing Problem with Time Windows

2015 ◽  
Vol 24 (06) ◽  
pp. 1550021 ◽  
Author(s):  
Esam Taha Yassen ◽  
Masri Ayob ◽  
Mohd Zakree Ahmad Nazri ◽  
Nasser R. Sabar
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Heuristic Algorithm ◽  
Vehicle Routing Problem ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Time Windows ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Routing Problem

Harmony search algorithm, which simulates the musical improvisation process in seeking agreeable harmony, is a population based meta-heuristics algorithm for solving optimization problems. Although it has been successfully applied on various optimization problems; it suffers the slow convergence problem, which greatly hinders its applicability for getting good quality solution. Therefore, in this work, we propose a hybrid meta-heuristic algorithm that hybridizes a harmony search with simulated annealing for the purpose of improving the performance of harmony search algorithm. Harmony search algorithm is used to explore the search spaces. Whilst, simulated annealing algorithm is used inside the harmony search algorithm to exploit the search space and further improve the solutions that are generated by harmony search algorithm. The performance of the proposed algorithm is tested using the Solomon's Vehicle Routing Problem with Time Windows (VRPTW) benchmark. Numerical results demonstrate that the hybrid approach is better than the harmony search without simulated annealing and the hybrid also proves itself to be more competent (if not better on some instances) when compared to other approaches in the literature.

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