Parallel simulated annealing for the vehicle routing problem with time windows

2003 ◽  
Author(s):  
Z.J. Czech ◽  
P. Czarnas
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Routing Problem ◽  
Parallel Simulated Annealing

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.

scholarly journals Hybrid Crow Search Algorithm - Simulated Annealing untuk Menyelesaikan Vehicle Routing Problem with Time Windows

2020 ◽  
Vol 2 (2) ◽  
pp. 97
Author(s):  
Bella Pristianisa Subari ◽  
Asri Bekti Pratiwi ◽  
Herry Suprajitno
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Routing Problem

Penulisan artikel ini bertujuan untuk menyelesaikan permasalahan Vehicle Routing Problem with Time Windows (VRPTW) dengan menggunakan Hybrid Crow Search Algorithm (CSA) dengan Simulated Annealing (SA). Hybrid CSA dengan SA adalah gabungan dari kedua algoritma dengan cara melakukan proses CSA kemudian hasil terburuknya diperbaiki dengan proses SA untuk sepuluh iterasi pertama. Proses algoritma ini dimulai dengan inisialisasi parameter, membangkitkan posisi dan memori awal, menghitung fungsi tujuan, memperbarui posisi gagak, menghitung fungsi tujuan posisi baru gagak, update memori gagak, menentukan solusi terburuk dari posisi gagak kemudian dilakukan modifikasi, hasil modifikasi dengan SA menggantikan solusi terburuk pada posisi gagak, proses berlanjut sampai maksimal iterasi dipenuhi dan menentukan solusi terbaik dari memori gagak. Berdasarkan hasil implementasi pada tiga tipe data dapat disimpulkan  bahwa semakin banyak jumlah iterasi, jumlah gagak, dan proses Simulated Annealing maka nilai fungsi tujuan yang diperoleh cenderung semakin baik, sedangkan nilai probabilitas kewaspadaan (AP) tidak memberikan pengaruh pada solusi permasalahan.

scholarly journals Optimal vehicle route schedules in picking up and delivering cargo containers considering time windows in logistics distribution networks: A case study

2020 ◽  
Vol 26 (4) ◽  
pp. 174-184
Author(s):  
Thi Diem Chau Le ◽  
Duy Duc Nguyen ◽  
Judit Oláh ◽  
Miklós Pakurár
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Vehicle Group ◽  
Real Problem ◽  
Routing Problem

AbstractThis study describes a pickup and delivery vehicle routing problem, considering time windows in reality. The problem of tractor truck routes is formulated by a mixed integer programming model. Besides this, three algorithms - a guided local search, a tabu search, and simulated annealing - are proposed as solutions. The aims of our study are to optimize the number of internal tractor trucks used, and create optimal routes in order to minimize total logistics costs, including the fixed and variable costs of an internal vehicle group and the renting cost of external vehicles. Besides, our study also evaluates both the quality of solutions and the time to find optimal solutions to select the best suitable algorithm for the real problem mentioned above. A novel mathematical model is formulated by OR tools for Python. Compared to the current solution, our results reduced total costs by 18%, increased the proportion of orders completed by internal vehicles (84%), and the proportion of orders delivered on time (100%). Our study provides a mathematical model with time constraints and large job volumes for a complex distribution network in reality. The proposed mathematical model provides effective solutions for making decisions at logistics companies. Furthermore, our study emphasizes that simulated annealing is a more suitable algorithm than the two others for this vehicle routing problem.

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.

scholarly journals Pengembangan Algoritma Hybrid Restart Simulated Annealing with Variable Neighborhood Search (HRSA-VNS) untuk penyelesaian kasus Vehicle Routing Problem with Time Windows (VRPTW)

2017 ◽  
Vol 6 (1) ◽  
pp. 49
Author(s):  
Titi Iswari
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Variable Neighborhood Search ◽  
Simulated Annealing Algorithm ◽  
Time Windows ◽  
Heuristic Method ◽  
Neighborhood Search ◽  
Routing Problem ◽  
Time Required

<p><em>Determining the vehicle routing is one of the important components in existing logistics systems. It is because the vehicle route problem has some effect on transportation costs and time required in the logistics system. In determining the vehicle routes, there are some restrictions faced, such as the maximum capacity of the vehicle and a time limit in which depot or customer has a limited or spesific opening hours (time windows). This problem referred to Vehicle Routing Problem with Time Windows (VRPTW). To solve the VRPTW, this study developed a meta-heuristic method called Hybrid Restart Simulated Annealing with Variable Neighborhood Search (HRSA-VNS). HRSA-VNS algorithm is a modification of Simulated Annealing algorithm by adding a restart strategy and using the VNS algorithm scheme in the stage of finding neighborhood solutions (neighborhood search phase). Testing the performance of HRSA-VNS algorithm is done by comparing the results of the algorithm to the Best Known Solution (BKS) and the usual SA algorithm without modification. From the results obtained, it is known that the algorithm perform well enough in resolving the VRPTW case with the average differences are -2.0% with BKS from Solomon website, 1.83% with BKS from Alvarenga, and -2.2% with usual SA algorithm without any modifications.</em></p><p><em>Keywords : vehicle routing problem, time windows, simulated annealing, VNS, restart</em></p>

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