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.

Harmony Search Algorithm for Vehicle Routing Problem with Time Windows

2013 ◽  
Vol 13 (4) ◽  
pp. 633-638 ◽  
Author(s):  
Esam Taha Yassen ◽  
Masri Ayob ◽  
Mohd Zakree Ahmad Nazr ◽  
Zulkifli Ahmad
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Routing Problem

Meta-harmony search algorithm for the vehicle routing problem with time windows

2015 ◽  
Vol 325 ◽  
pp. 140-158 ◽  
Author(s):  
Esam Taha Yassen ◽  
Masri Ayob ◽  
Mohd Zakree Ahmad Nazri ◽  
Nasser R. Sabar
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Routing Problem

scholarly journals A Modified Harmony Search Algorithm for Solving the Dynamic Vehicle Routing Problem with Time Windows

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Shifeng Chen ◽  
Rong Chen ◽  
Jian Gao
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Harmony Search ◽  
Population Diversity ◽  
Benchmark Problems ◽  
Dynamic Vehicle Routing ◽  
Dynamic Vehicle Routing Problem ◽  
Routing Problem

The Vehicle Routing Problem (VRP) is a classical combinatorial optimization problem. It is usually modelled in a static fashion; however, in practice, new requests by customers arrive after the initial workday plan is in progress. In this case, routes must be replanned dynamically. This paper investigates the Dynamic Vehicle Routing Problem with Time Windows (DVRPTW) in which customers’ requests either can be known at the beginning of working day or occur dynamically over time. We propose a hybrid heuristic algorithm that combines the harmony search (HS) algorithm and the Variable Neighbourhood Descent (VND) algorithm. It uses the HS to provide global exploration capabilities and uses the VND for its local search capability. In order to prevent premature convergence of the solution, we evaluate the population diversity by using entropy. Computational results on the Lackner benchmark problems show that the proposed algorithm is competitive with the best existing algorithms from the literature.

Quantum Inspired Algorithm for a VRP with Heterogeneous Fleet Mixed Backhauls and Time Windows

2016 ◽  
Vol 7 (4) ◽  
pp. 18-38 ◽  
Author(s):  
Meryem Berghida ◽  
Abdelmadjid Boukra
Keyword(s):  
Population Size ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Time Windows ◽  
Harmony Search ◽  
Routing Problem ◽  
Heterogeneous Fleet ◽  
Variable Population ◽  
Variable Population Size

This paper presents a new Quantum Inspired Harmony Search algorithm with Variable Population Size QIHSVPS for a complex variant of vehicle routing problem (VRP), called HVRPMBTW (Vehicle Routing Problem with Heterogeneous fleet, Mixed Backhauls and Time Windows). This variant is characterized by a limited number of vehicles with various capacities and costs. The vehicles serve two types of customers: linehauls customers and backhauls customers. Each customer must be visited in a specific interval of time. The authors propose to use quantum principles to accelerate evolution process and variable population size to decrease the number of solution's evaluation, when the improvement is insignificant. This new approach was tested on benchmarks and produces satisfactory results compared to other approaches.

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 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 Optimization of a Capacitated Vehicle Routing Problem for Municipal Solid Waste Collection Using an Intelligence Hybrid Harmony Search Algorithm

2021 ◽  
Author(s):  
Wullapa Wongsinlatam ◽  
Ayuwat Thanasate-angkool
Keyword(s):  
Vehicle Routing ◽  
Carbon Emissions ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Harmony Search ◽  
Harmony Search Algorithm ◽  
Fixed Costs ◽  
Routing Problem ◽  
Penalty Costs ◽  
Capacitated Vehicle

Abstract The study of sustainable management of municipal solid waste (MSW) collection has been increasing in recent years. However, the focus areas of research are mostly in the economics and environmental dimensions. This paper adds social aspects of MSW into considerations to accelerate more comprehensive decision making. The consideration on the capacity and fixed costs of vehicles, the distances from depot to the disposal facilities are determined in this paper. The environmental issues relating to fuel consumption, carbon emissions, and the evaluation of social impact from the penalty costs of imbalanced trip assignments are also determined to adopt a comprehensive solution to the capacitated vehicle routing problem (CVRP) model. Then, the optimization model of MSW collection is proposed to minimize management costs which compose of the fixed costs of vehicles, fuel consumption costs, carbon emissions costs, and penalty costs. In this paper, two metaheuristic techniques are used to optimization the CVRP model in the MSW collection system. A new metaheuristic algorithm, called an intelligence hybrid harmony search algorithm (IHHS), is proposed in comparison with the standard harmony search (SHS) algorithm. The result shows that the IHHS algorithm can obtain the global optimal solution and can minimize the total objective function for the CVRP model.

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