Multiobjective capacitated green vehicle routing problem with fuzzy time-distances and demands split into bags

Gupta, Pankaj; Govindan, Kannan; Mehlawat, Mukesh Kumar; Khaitan, Anisha

doi:10.1080/00207543.2021.1888392

Cited by 30 publications

(12 citation statements)

References 61 publications

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“…2020) developed a single-objective mathematical model for routing electric capacitated vehicles and solved using the GA algorithm. Gupta et al (2021) introduced a multi-objective multi-depot mathematical model for vehicle routing. Karakati c (2021) proposed a mathematical model for charging electric vehicles and used a GA to solve it.…”

Section: Literature Reviewmentioning

confidence: 99%

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

Zahedi

Kia

Khalilzadeh³

2023

JAMR

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PurposeThe vehicle routing problem (VRP) has been widely investigated during last decades to reduce logistics costs and improve service level. In addition, many researchers have realized the importance of green logistic system design in decreasing environmental pollution and achieving sustainable development.Design/methodology/approachIn this paper, a bi-objective mathematical model is developed for the capacitated electric VRP with time windows and partial recharge. The first objective deals with minimizing the route to reduce the costs related to vehicles, while the second objective minimizes the delay of arrival vehicles to depots based on the soft time window. A hybrid metaheuristic algorithm including non-dominated sorting genetic algorithm (NSGA-II) and teaching-learning-based optimization (TLBO), called NSGA-II-TLBO, is proposed for solving this problem. The Taguchi method is used to adjust the parameters of algorithms. Several numerical instances in different sizes are solved and the performance of the proposed algorithm is compared to NSGA-II and multi-objective simulated annealing (MOSA) as two well-known algorithms based on the five indexes including time, mean ideal distance (MID), diversity, spacing and the Rate of Achievement to two objectives Simultaneously (RAS).FindingsThe results demonstrate that the hybrid algorithm outperforms terms of spacing and RAS indexes with p-value <0.04. However, MOSA and NSGA-II algorithms have better performance in terms of central processing unit (CPU) time index. In addition, there is no meaningful difference between the algorithms in terms of MID and diversity indexes. Finally, the impacts of changing the parameters of the model on the results are investigated by performing sensitivity analysis.Originality/valueIn this research, an environment-friendly transportation system is addressed by presenting a bi-objective mathematical model for the routing problem of an electric capacitated vehicle considering the time windows with the possibility of recharging.

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Section: Literature Reviewmentioning

confidence: 99%

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

Zahedi

Kia

Khalilzadeh³

2023

JAMR

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“…A logistics management system is one that coordinates the movement of goods between origins and the destinations (consumption points), so that requirements of customers or corporates can be complied. In other words, logistics is the management of the goods' flow from the origin to the consumption in transportation and business terms to comply requirements of customers, consumers, cooperators, and companies (Gupta et al, 2021; Perotti et al, 2022). The significance of logistics management in a supply chain network is becoming clearer for both managers as well as academic experts.…”

Section: Introductionmentioning

confidence: 99%

Outsourcing logistics operations in circular economy towards to sustainable development goals

et al. 2022

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One of novel manners to achieve sustainable development is concentrating on circular economy in order to manage greenhouse gas emissions, energy consumption, and waste. It also helps to protect the environment and optimize usage of input resources. The main element of circular economy is closed-loop supply chain which covers both forward and reverse products flows. This study aims to outsource logistics operations in a closed-loop supply chain. An innovative analytical multi-step fuzzy decision-making method is proposed to rank sustainable third-party logistics

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“…Dantzig and Ramser [5] first proposed the problem of vehicle routing in 1959. This is a combination of the two issues of the traveling salesman (unlimited consideration of vehicle capacity) and the packing of boxes (zero consideration of freight costs on the ridges), trying to optimally design a set of routes for the transport fleet in such a way that a certain number of customers to be served and has different side restrictions [6]. The variety of this problem is so great that it is challenging and timeconsuming to classify them and express the various states in which it occurs.…”

Section: Introductionmentioning

confidence: 99%

A Neutrosophic Fuzzy Programming Method to Solve a Multi-depot Vehicle Routing Model under Uncertainty during the COVID-19 Pandemic

Nozari

Tavakkoli–Moghaddam

Ghahremani-Nahr

2022

IJE

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T he worldwide prevalence of coronavirus disease and the severe problems in the distribution of medical equipment have led to the modeling of multi-depot vehicle routing under uncertainty in the COVID-19 pandemic. T he primary purpose of the proposed model is to locate warehouses and production centers and route vehicles for the distribution of medical goods to hospitals. A robust fuzzy method controls uncertain parameters, such as demand, transmission, and distribution costs. T he effect of uncertainty using a neutrosophic fuzzy programming method shows that by increasing demand, the volume of medical goods exchanges and the number of vehicles used to distribute goods increase. T his leads to an increase in the total cost of the problem and the amount of greenhouse gas (GHG) emissions. T he results also show that using more vehicles reduces staff fatigue to distribute medical products and reduces the prevalence of the COVID-19 pandemic. In the most important sensitivity analysis of the problem on the capacity of the vehicle, it was determined that by increasing the capacity of the vehicle, fewer vehicles are used, and as a result, the cost and amount of greenhouse gas emissions are reduced. On the other hand, this has led to a decrease in the prevalence of the COVID-19 virus.

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Multiobjective capacitated green vehicle routing problem with fuzzy time-distances and demands split into bags

Cited by 30 publications

References 61 publications

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

Outsourcing logistics operations in circular economy towards to sustainable development goals

A Neutrosophic Fuzzy Programming Method to Solve a Multi-depot Vehicle Routing Model under Uncertainty during the COVID-19 Pandemic

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