scholarly journals A Simulated Annealing Algorithm for Solving Two-Echelon Vehicle Routing Problem with Locker Facilities

Algorithms ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 218
Author(s):  
A. A. N. Perwira Redi ◽  
Parida Jewpanya ◽  
Adji Candra Kurniawan ◽  
Satria Fadil Persada ◽  
Reny Nadlifatin ◽  
...  
Keyword(s):  
Simulated Annealing ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Simulated Annealing Algorithm ◽  
Two Phase ◽  
Routing Problem ◽  
Intermediate Facilities ◽  
Annealing Algorithm ◽  
Phase Optimization ◽  
The Cost

We consider the problem of utilizing the parcel locker network for the logistics solution in the metropolitan area. Two-echelon distribution systems are attractive from an economic standpoint, whereas the product from the depot can be distributed from or to intermediate facilities. In this case, the intermediate facilities are considered as locker facilities present in an accessible location in the vicinity of the final customers. In addition, the utilization of locker facilities can reduce the cost caused by the unattended deliveries. The problem is addressed as an optimization model that formulated into an integer linear programming model denoted as the two-echelon vehicle routing problem with locker facilities (2EVRP-LF). The objective is to minimize the cost of transportation with regards to the vehicle travelling cost, the intermediate facilities renting cost, and the additional cost to compensate the customer that needs to travel to access the intermediate facilities. Because of its complexity, a simulated annealing algorithm is proposed to solve the problem. On the other hand, the modelling approach can be conducted by generating two-phase optimization model approaches, which are the p-median problem and the capacitated vehicle routing problem. The results from both methods are compared in numerical experiments. The results show the effectiveness of 2EVRP-LF compared to the two-phase optimization. Furthermore, the simulated annealing algorithm showed an effective performance in solving 2EVRP-LF.

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).

scholarly journals Algoritma Simulated Annealing untuk Menentukan Rute Kendaraan Heterogen (Studi Kasus)

2020 ◽  
Vol 7 (5) ◽  
pp. 933
Author(s):  
Andriansyah Andriansyah ◽  
Rizky Novatama ◽  
Prima Denny Sentia
Keyword(s):  
Supply Chain ◽  
Simulated Annealing ◽  
Vehicle Routing ◽  
Heuristic Algorithm ◽  
Vehicle Routing Problem ◽  
Simulated Annealing Algorithm ◽  
Routing Problem ◽  
Annealing Algorithm ◽  
Banda Aceh ◽  
Insertion Heuristic

<p>Permasalahan transportasi dalam supply chain management sangat penting untuk dikaji karena dapat menimbulkan biaya logistik yang sangat besar. Salah satu cara untuk mengurangi biaya transportasi adalah dengan penentuan rute kendaraan atau dikenal dengan istilah vehicle routing problem. Objek yang menjadi kajian merupakan perusahaan yang bergerak pada bidang distribusi produk untuk area kota Banda Aceh dan sekitarnya. Dalam proses distribusi, perusahaan ini menggunakan dua jenis kendaraan dengan kapasitas dan biaya operasional yang berbeda sehingga permasalahan menjadi heterogeneous fleet vehicle routing problem. Penentuan rute kendaraan dalam penelitian ini dilakukan dengan tiga metode, yaitu metode analitik, algoritma insertion heuristic sebagai metode heuristik, dan algoritma simulated annealing sebagai metode metaheuristik. Berdasarkan hasil yang diperoleh dari data ujicoba, algoritma simulated annealing merupakan algoritma yang paling baik dalam menyelesaikan permasalahan. Secara rata-rata, algoritma simulated annealing dapat menghasilkan kualitas solusi yang sama dengan metode analitik, namun dengan waktu komputasi yang lebih singkat. Selain itu, algoritma simulated annealing menghasilkan kualitas solusi yang lebih baik dibandingkan algoritma insertion heuristic yang dikembangkan dalam penelitian dan dapat meningkatkkan kualitas solusi sebesar 20,18% dari penelitian sebelumnya dengan waktu komputasi 19,27 detik.</p><p> </p><p><em><strong>Abstract</strong></em></p><p class="Judul2"><em>Transportation problems </em><em>in supply chain </em><em>are very important </em><em>to be discussed </em><em>because </em><em>they </em><em>can </em><em>raises</em><em> enormous logistic cost. </em><em>Route determination of the vehicles known as vehicle routing problem is the one of ways to reduce transportation cost</em><em>. </em><em>The object discussed in this study is the distribution company</em><em> </em><em>for Banda Aceh city and its surroundings</em><em>.</em><em> The company uses two types of vehicle to distribute the product for customers.</em><em> </em><em>The differences each vehicle are vehicle capacity and operational cost. To cover these differences, the problem becomes heterogenous fleet vehicle routing problem. The study uses three methods to solve the problem. Analitycal method, insertion heuristic algorithm as heuristic method and simulated annealing algorithm as metaheuristic method are the methods used. According to the results, simulated anneling algorithm produces the better solutions than two others. On average, solutions produced by simulated annealing algorithm from dataset have same quality with analitycal method, but with faster computation. Furthermore, </em><em>simulated anneling </em><em>algorithm </em><em>produces better quality of solutions than insertion heuristic algorithm both from this stu</em><em>dy and previous study. The solution improves 20,18% with computation time 19,27 seconds.</em></p><p class="Judul2"> </p><p><em><strong><br /></strong></em></p><p class="Abstrak" align="center"> </p>

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