Multi-Objective Green Mixed Vehicle Routing Problem Under Rough Environment

Dutta, Joydeep; Barma, Partha Sarathi; Mukherjee, Anupam; Kar, Samarjit; De, Tanmay; Pamučar, Dragan; Šukevičius, Šarūnas; Garbinčius, Giedrius

doi:10.3846/transport.2021.14464

Cited by 14 publications

(8 citation statements)

References 39 publications

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“…The following is the mathematical model of the biobjective GVRP studied in this paper. A very similar mathematical model is found in Dutta et al (2021).…”

Section: Mathematical Modelsupporting

confidence: 57%

“…They, too, evaluated the efficiency of their results according to the HV metric. Dutta et al (2021) developed their previous SOVRP study (Dutta et al, 2019) and studied a multiobjective GVRP (MOGVRP) having two objectives: minimization of total distance and minimization of carbon emissions of the vehicle fleet. They used the FCR proposed in Xiao et al (2012) for the latter objective function.…”

Section: Literature Reviewmentioning

confidence: 99%

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Bi‐objective green vehicle routing problem

Erdoğdu

Karabulut

2021

Int Trans Operational Res

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The green vehicle routing problem (GVRP) is a variant of the vehicle routing problem (VRP), which increasingly attracts many researchers in recent years due to the growing global environmental issues. As the transportation of the products grows, the number of vehicles in fleets and the pollutants caused by these vehicles also grow, which in turn negatively affects human health. In this paper, a biobjective GVRP was studied. The two objectives are minimizing the total distance and minimizing the total fuel consumption of all vehicle routes. As a solution method, an adaptive large neighborhood search was hybridized with two new local search heuristics. The proposed method was applied to two well‐known benchmark problem sets for VRPs and new approximate Pareto fronts were obtained for these benchmark sets.

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“…The following is the mathematical model of the biobjective GVRP studied in this paper. A very similar mathematical model is found in Dutta et al (2021).…”

Section: Mathematical Modelsupporting

confidence: 57%

Section: Literature Reviewmentioning

confidence: 99%

Bi‐objective green vehicle routing problem

Erdoğdu

Karabulut

2021

Int Trans Operational Res

View full text Add to dashboard Cite

show abstract

“…MOP-VRP is not an exception. Several approaches are available to MOP [19] (including MOP-VRP [20,21]). Generally, they are classified into the following: (1) The preference approach, where decision makers have the higher information needed to select the final solution from among several options.…”

Section: The Optimization Model Was Based On Several Assumptions That...mentioning

confidence: 99%

Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem

Son

Jaafar

Aziz

et al. 2022

Entropy

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The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially logistics. In this study, we introduced an adaptive method to a complex VRP. It combines multi-objective optimization and several forms of VRPs with practical requirements for an urban shipment system. The optimizer needs to consider terrain and traffic conditions. The proposed model also considers customers’ expectations and shipper considerations as goals, and a common goal such as transportation cost. We offered compromise programming to approach the multi-objective problem by decomposing the original multi-objective problem into a minimized distance-based problem. We designed a hybrid version of the genetic algorithm with the local search algorithm to solve the proposed problem. We evaluated the effectiveness of the proposed algorithm with the Tabu Search algorithm and the original genetic algorithm on the tested dataset. The results show that our method is an effective decision-making tool for the multi-objective VRP and an effective solver for the new variation of VRP.

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“…The MOP-VRP is not an exception. Several approaches are available to the MOP [19] (including MOP-VRP [20], [21]). Generally, they are classified into (1) the preferred approach, where decision-makers have the higher information to select the final solution among several options.…”

Section: Related Workmentioning

confidence: 99%

Metaheuristic Algorithms Based on Compromise Programming for Multi-Objective Urban Shipment Problem

Son¹,

Jaafar²,

Aziz³

et al. 2022

Preprint

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The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially logistics. In this study, we introduced an adaptive method to a complex VRP. It combines multi-objective optimization and several forms of VRPs with practical requirements for an urban shipment system. The optimizer needs to consider terrain and traffic conditions. The proposed model also considers customers' expectations, shipper considerations as goals, and the common goal like transportation cost. We offered compromise programming to approach the multi-objective problem by decomposing the original multi-objective problem into a minimized distance-based problem. We designed a hybrid version of the Genetic algorithm with the Local Search algorithm to solve the proposed problem. We evaluate the effectiveness of the proposed algorithm with the Tabu Search algorithm, the original Genetic algorithm on the tested dataset. The results show that our method is an effective decision-making tool for the multi-objective VRP and an effective solver for the new variation of VRP.

show abstract

Multi-Objective Green Mixed Vehicle Routing Problem Under Rough Environment

Cited by 14 publications

References 39 publications

Bi‐objective green vehicle routing problem

Bi‐objective green vehicle routing problem

Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem

Metaheuristic Algorithms Based on Compromise Programming for Multi-Objective Urban Shipment Problem

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