Bi‐objective green vehicle routing problem

Erdoğdu, Kazım; Karabulut, Korhan

doi:10.1111/itor.13044

Cited by 13 publications

(6 citation statements)

References 38 publications

(106 reference statements)

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“…The literature [10][11][12][13][14][15][16][17] provides a large number of solution ideas for workshop material distribution problems from the distribution method, distribution model, and algorithm model. Although the above research has made some progress, there are still problems, such as poor solution quality, easy falls into local optimal, and no consideration of environmental factors.…”

Section: Comparison With Previous Literaturementioning

confidence: 99%

“…Taking a refrigerator assembly line as an example, the feasibility and effectiveness of the proposed method were verified. Erdodu et al [14] studied the green vehicle routing problem, aiming to minimize the total distance and the total fuel consumption of all vehicle routes. The adaptive large neighborhood search was hybridized with two new local search heuristic methods, which were verified by comparison with other similar literature.…”

Section: Introductionmentioning

confidence: 99%

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Low-Carbon and Energy-Saving Path Optimization Scheduling of Material Distribution in Machining Shop Based on Business Compass Model

Xiao,

Zhang,

Wang

2023

Processes

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In order to reduce carbon emission and energy consumption in the process of raw material distribution, the workshop material distribution management model was established based on the business compass model; it can help guide enterprises to manage workshop production. Based on the raw material distribution equipment, a path calculation model considering the carbon emission and energy consumption in the process of raw material distribution was established. The dung beetle optimizer was selected for the optimization calculation. The dung beetle optimizer has the characteristics of fast convergence and high solution accuracy. The material distribution of an engine assembly workshop was taken as an example; the results showed that the optimized scheduling model could effectively optimize the material distribution route and reduce energy consumption and carbon emission in the distribution process on the basis of meeting the distribution demand.

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Section: Comparison With Previous Literaturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Low-Carbon and Energy-Saving Path Optimization Scheduling of Material Distribution in Machining Shop Based on Business Compass Model

Xiao,

Zhang,

Wang

2023

Processes

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“…(2021), Amaruchkul (2021), Xiang et al. (2021), Erdoǧdu and Karabulut (2021), Bissoli et al. (2021) and Queiroz and Mundim (2020) for very recent applications.…”

Section: Introductionmentioning

confidence: 99%

“…The increasing necessity of dealing with this type of problem has influenced the strong development of the field of multi-objective optimisation in recent years. The reader is referred to Salamirad et al (2021), Amaruchkul (2021), Xiang et al (2021), Erdoǧdu and Karabulut (2021), Bissoli et al (2021) and Queiroz and Mundim (2020) for very recent applications. In this work, we focus on a particularly appealing problem: the bi-objective minimum spanning tree (BMST) problem that has applications in different contexts.…”

Section: Introductionmentioning

confidence: 99%

Two‐phase strategies for the bi‐objective minimum spanning tree problem

Amorosi

Puerto

2022

Int Trans Operational Res

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This paper presents a new two-phase algorithm for the bi-objective minimum spanning tree (BMST) problem. In the first phase, it computes the extreme supported efficient solutions resorting to both mathematical programming and algorithmic approaches, while the second phase is devoted to obtaining the remaining efficient solutions (non-extreme supported and non-supported). This latter phase is based on a new recursive procedure capable of generating all the spanning trees of a connected graph through edge interchanges based on increasing evaluation of non-zero reduced costs of associated weighted linear programs. Such a procedure exploits a common property of a wider class of problems to which the minimum spanning tree (MST) problem belongs, that is the spanning tree structure of its basic feasible solutions. Computational experiments are conducted on different families of graphs and with different types of cost. These results show that this new two-phase algorithm is correct, very easy to implement and it allows one to extract conclusions on the difficulty of finding the entire set of Pareto solutions of the BMST problem depending on the graph topology and the possible correlation of the edge costs.

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“…In this study, existing datasets were used to evaluate the performance of the proposed approach. Erdoğdu and Karabulut (2022) extended the work of Xiao et al (2012) and studied their GVRP with an objective function that minimized the total distance and total fuel consumption of all vehicle routes. As a solution method, they used ALNS with two new local search heuristics and applied it to two well-known benchmark problem sets for VRPs.…”

Section: Introductionmentioning

confidence: 99%

Solving vehicle routing problem with time windows using metaheuristic approaches

Birecik

Özgen

2022

IJICC

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PurposeDrugs are strategic products with essential functions in human health. An optimum design of the pharmaceutical supply chain is critical to avoid economic damage and adverse effects on human health. The vehicle-routing problem, focused on finding the lowest-cost routes with available vehicles and constraints, such as time constraints and road length, is an important aspect of this. In this paper, the vehicle routing problem (VRP) for a pharmaceutical company in Turkey is discussed.Design/methodology/approachA mixed-integer programming (MIP) model based on the vehicle routing problem with time windows (VRPTW) is presented, aiming to minimize the total route cost with certain constraints. As the model provides an optimum solution for small problem sizes with the GUROBI® solver, for large problem sizes, metaheuristic methods that simulate annealing and adaptive large neighborhood search algorithms are proposed. A real dataset was used to analyze the effectiveness of the metaheuristic algorithms. The proposed simulated annealing (SA) and adaptive large neighborhood search (ALNS) were evaluated and compared against GUROBI® and each other through a set of real problem instances.FindingsThe model is solved optimally for a small-sized dataset with exact algorithms; for solving a larger dataset, however, metaheuristic algorithms require significantly lesser time. For the problem addressed in this study, while the metaheuristic algorithms obtained the optimum solution in less than one minute, the solution in the GUROBI® solver was limited to one hour and three hours, and no solution could be obtained in this time interval.Originality/valueThe VRPTW problem presented in this paper is a real-life problem. The vehicle fleet owned by the factory cannot be transported between certain suppliers, which complicates the solution of the problem.

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Bi‐objective green vehicle routing problem

Cited by 13 publications

References 38 publications

Low-Carbon and Energy-Saving Path Optimization Scheduling of Material Distribution in Machining Shop Based on Business Compass Model

Low-Carbon and Energy-Saving Path Optimization Scheduling of Material Distribution in Machining Shop Based on Business Compass Model

Two‐phase strategies for the bi‐objective minimum spanning tree problem

Solving vehicle routing problem with time windows using metaheuristic approaches

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