A new efficient approach for solving the capacitated Vehicle Routing Problem using the Gravitational Emulation Local Search Algorithm

Hosseinabadi, Ali Asghar Rahmani; Rostami, Najmeh Sadat Hosseini; Kardgar, Maryam; Mirkamali, Seyed Saeid; Abraham, Ajith

doi:10.1016/j.apm.2017.02.042

Cited by 42 publications

(16 citation statements)

References 29 publications

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“…Since the emergence of "truck dispatching problem," vehicle routing problem (VRP) has been a hot research field [2]. And many heuristic algorithms were developed to solve VRP [3]. Our paper is mainly relevant to two topics: green vehicle routing problem and routing with UAVs, which are reviewed below.…”

Section: Literature Reviewmentioning

confidence: 99%

“…ere are 20 customers who should be satisfied. We encode them as {1, 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19, 20} and the warehouse as 0. As only 1 pair of a UAV and a vehicle is needed, they serve the whole delivery area.…”

Section: Initial Population Generationmentioning

confidence: 99%

“…Finally, they go right to the seventh subarea to serve customers from left to right and go up to the eighth to serve customers from right to left and go back to the warehouse. Now, we obtain the service sequence codes as {18, 1,3,7,9,19,6,12,16,8,14,2,13,15,20,11,17,4,5,10} (Figure 1). en, we randomly generate the group codes as {2,5,3,4,5,1}.…”

Section: Initial Population Generationmentioning

confidence: 99%

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Impact of UAV Delivery on Sustainability and Costs under Traffic Restrictions

Yang

Huang

2020

Mathematical Problems in Engineering

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Compared with traditional vehicles delivery, unmanned aerial vehicle (UAV) delivery can reduce energy consumption and greenhouse gas emissions, which benefits environmental sustainability. Besides, UAVs can overcome traffic restrictions, which are the big obstacle in parcel delivery. In reality, there are two kinds of most popular traffic restrictions, vehicle-type restriction, and half-side traffic. We propose a mixed-integer (0-1 linear) green routing model with these two kinds of traffic restrictions for UAVs to exploit the environmental aspects of the use of UAVs in logistics. A genetic algorithm is proposed to efficiently solve the complex routing problem, and an experimental analysis is made to illustrate and validate our model and the algorithm. We found that, under both these two traffic restrictions, UAV delivery can accomplish deliveries that cannot be carried out or are carried out at much higher costs by vehicles only and can always effectively save costs and cut CO2 emissions, which is environmentally friendly. Furthermore, UAV delivery saves more cost and cuts more CO2 emission under the first kind of traffic restriction than that under the second.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Initial Population Generationmentioning

confidence: 99%

Section: Initial Population Generationmentioning

confidence: 99%

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Impact of UAV Delivery on Sustainability and Costs under Traffic Restrictions

Yang

Huang

2020

Mathematical Problems in Engineering

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“…As it was mentioned, there are many applied metaheuristics presented in order to solve the optimization problems similar to the research problem [44][45][46][47][48][49]. Since the applicability and the robustness of the GA algorithms have been proved and it has generated appropriate solutions for CARPs in the literature [50][51][52][53][54], GA is proposed as the main algorithm for the current research.…”

Section: Hybrid Genetic Algorithm (Hga)mentioning

confidence: 99%

A Hybrid Genetic Algorithm for Multi-Trip Green Capacitated Arc Routing Problem in the Scope of Urban Services

et al. 2018

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Greenhouse gases (GHG) are the main reason for the global warming during the past decades. On the other hand, establishing a well-structured transportation system will yield to create least cost-pollution. This paper addresses a novel model for the multi-trip Green Capacitated Arc Routing Problem (G-CARP) with the aim of minimizing total cost including the cost of generation and emission of greenhouse gases, the cost of vehicle usage and routing cost. The cost of generation and emission of greenhouse gases is based on the calculation of the amount of carbon dioxide emitted from vehicles, which depends on such factors as the vehicle speed, weather conditions, load on the vehicle and traveled distance. The main applications of this problem are in municipalities for urban waste collection, road surface marking and so forth. Due to NP-hardness of the problem, a Hybrid Genetic Algorithm (HGA) is developed, wherein a heuristic and simulated annealing algorithm are applied to generate initial solutions and a Genetic Algorithm (GA) is then used to generate the best possible solution. The obtained numerical results indicate that the proposed algorithm could present desirable performance within a suitable computational run time. Finally, a sensitivity analysis is implemented on the maximum available time of the vehicles in order to determine the optimal policy.

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“…The problem has several applications including the meal delivery, the waste collection and the school bus routing problems (Jabali et al 2015;Bae and Moon 2016;Buhrkal et al 2012;Hiermann et al 2016). The vehicles are capacitated in the CVRP, and several applications, namely road transportation and network routing problems, have been introduced for this problem (Faulin et al 2011;Sörensen and Schittekat 2013;Hosseinabadi et al 2017). The MDVRP uses multiple depots instead of one depot to construct the routes.…”

mentioning

confidence: 99%

Time-constrained maximal covering routing problem

Amiri

Salari

2018

OR Spectrum

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We introduce the time-constrained maximal covering routing problem (TCMCRP), as a generalization of the covering salesman problem. In this problem, we are given a central depot, a set of facilities and several customers which are located within a pre-determined coverage distance of available facilities. Each facility can supply the demand of some customers which are within its coverage radius. Starting from the depot, the goal is to maximize the total number of covered customers, by constructing a set of p length constraint Hamiltonian cycles. We have proposed a mixed integer linear programming model and three heuristic algorithms, namely iterated local search (ILS), tabu search (TS) and variable neighborhood search (VNS), to solve the problem. Extensive computational tests on this problem and some of its variants clearly indicate the effectiveness of the developed solution methods.

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A new efficient approach for solving the capacitated Vehicle Routing Problem using the Gravitational Emulation Local Search Algorithm

Cited by 42 publications

References 29 publications

Impact of UAV Delivery on Sustainability and Costs under Traffic Restrictions

Impact of UAV Delivery on Sustainability and Costs under Traffic Restrictions

A Hybrid Genetic Algorithm for Multi-Trip Green Capacitated Arc Routing Problem in the Scope of Urban Services

Time-constrained maximal covering routing problem

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