A metaheuristic algorithm for the multi-depot vehicle routing problem with heterogeneous fleet

Bolaños, Rubén Iván; Escobar, John Willmer; Echeverri, Mauricio Granada

doi:10.5267/j.ijiec.2017.11.005

Cited by 18 publications

(7 citation statements)

References 33 publications

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“…One of the well-known variants of the CVRP is the multi-depot vehicle routing problem (MDVRP), which has been extensively studied (Escobar et al, 2014a;Chávez et al, 2016;Bolanos et al, 2018;. In the MDVRP, there are several possible starting points for the vehicles, and therefore, each customer is assigned a route from one of the available depots.…”

Section: Literature Reviewmentioning

confidence: 99%

Metaheuristic algorithm for the location, routing and packing problem in the collection of recyclable waste

Herrera-Cobo¹,

Escobar²,

Álvarez‐Martínez³

2023

10.5267/j.ijiec

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The increasing accumulation of solid waste worldwide has made it necessary to look for alternatives that improve the operation of recyclable waste collection systems to make waste treatment more profitable and eco-friendlier. This paper introduces a new variant of the multi-compartment vehicle routing problem (MCVRP) that considers the rearrangement or relocation of collection points and packing the demand. This problem is called the location packing multi-compartment vehicle routing problem (LPMCVRP) and is developed for a waste collection system using vehicles with flexible compartments. A mathematical formulation of the problem is proposed. A two-phase metaheuristic algorithm based on a tabu search without packing considerations and a variant that integrates a tabu search and a greedy randomized adaptive search procedure (GRASP) scheme with packing constraints have been proposed. A set of instances adapted from the literature is generated to validate the proposed solution strategy. The results obtained show the efficiency of the proposed solution scheme for optimizing collection systems.

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Section: Literature Reviewmentioning

confidence: 99%

Metaheuristic algorithm for the location, routing and packing problem in the collection of recyclable waste

Herrera-Cobo¹,

Escobar²,

Álvarez‐Martínez³

2023

10.5267/j.ijiec

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“…For examples, research from Kaabachi, Jriji, and Krichen (2017) has improved the ACO by adding local search to solve the problem. Besides that, Iván, Willmer, and Granada (2018) make modification on GA to find the minimal distance of routes by producing an initial population with heuristic solutions acquired from the heuristic algorithm. Yalian (2016) was improved based on the performance of ACO by using smooth mechanism and 3-opt algorithm for improving the local search strategy.…”

Section: Gamentioning

confidence: 99%

A Review of Single and Population-Based Metaheuristic Algorithms Solving Multi Depot Vehicle Routing Problem

Samsuddin

Othman

Yusuf

2018

IJSECS

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Multi-Depot Vehicle Routing Problem (MDVRP) arises with rapid development in the logistics and transportation field in recent years. This field, mainly, faces challenges in arranging their fleet efficiently to distribute the goods to customers by minimizing distance and cost. Therefore, the decision maker needs to specify the vehicles to reach the particular depot which, serves the customers with the predetermined capacity. Hence, to solve the stated problems, there is a need to apply metaheuristic methods to get minimal transportation costs. This article reviews on single and population-based metaheuristic methods solving MDVRP from the year 2013 until 2018. The methods discussed were simulated annealing (SA), variable neighborhood search (VNS), ant colony algorithm (ACO), particle swarm optimization (PSO) and genetic algorithm (GA). From the previous works, it can be concluded that the application of populationbased metaheuristic gives better solutions in solving MDVRPs.

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“…The authors claimed their approach could be generalized for boarder applications. Additional works (Arabi, Dehshiri, & Shokrgozar, 2018;Bolaños, Escobar, & Echeverri, 2018;Chiu, Wu, & Tseng, 2019b;Morales, Franco, & Mendez-Giraldo, 2018;Nielsen & Saha, 2018;Paz, Granada-Echeverri, & Escobar, 2018;Puška, Kozarević, Stević, & Stovrag, 2018;Stažnik, Babić, & Bajor, 2017;Zhao, Qian, Nakamura, & Nakagawa, 2018) studied the influence of distinct features of multiple deliveries on various types of manufacturingtransportation and supply-chain systems. Few prior works have investigated the joint influence of breakdowns, outsourcing, multiple deliveries, and rework/disposal of defective stocks on the optimal batch-fabrication runtime decision, this work aims to fill the gap.…”

Section: Introductionmentioning

confidence: 99%

Optimal hybrid inventory replenishment runtime for a vendor- buyer coordinated system with breakdowns and rework/disposal of nonconforming items

Chiu

Sung

2020

JART

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Most multinational/transnational manufacturers that own internal supply chains and operate in turbulent world markets apply strategies related to product quality, low-cost, and timely delivery. This study aims to assist such firms with making accurate decisions to enable their competitive strategies and cope with the realities of limited capacity and unreliable equipment. We examine a vendor-buyer coordinated system featuring batch fabrication, outsourcing, quality reassurance, discontinuous deliveries, and an unreliable machine. The system outsources a portion of a lot to reduce manufacturing uptime, and the in-house fabrication system experiences undesirable defective items and Poisson distributed breakdowns. In each cycle, corrective action and rework/disposal of defective stocks are undertaken as these incidents occur, and upon receipt of outsourced products and when the entire batch is quality ensured, it makes multiple deliveries of the end products. Using modeling, formulation, derivation, and an optimization methodology, we obtain the problem’s cost function and justify its convexity. We then apply differential calculus and propose a recursive algorithm to derive the problem’s optimal replenishment runtime. A numerical illustration is offered to show the applicability of the result that reveals various important system characteristics/ capabilities, such as the distinct and combined influences of breakdowns, outsourcing, rework, scrap, and delivery-frequency factors on various system parameters, performance, and optimal runtime. The methods proposed here can facilitate managerial operations planning and strategic decision making in an intra-supply chain setting in practice.

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A metaheuristic algorithm for the multi-depot vehicle routing problem with heterogeneous fleet

Cited by 18 publications

References 33 publications

Metaheuristic algorithm for the location, routing and packing problem in the collection of recyclable waste

Metaheuristic algorithm for the location, routing and packing problem in the collection of recyclable waste

A Review of Single and Population-Based Metaheuristic Algorithms Solving Multi Depot Vehicle Routing Problem

Optimal hybrid inventory replenishment runtime for a vendor- buyer coordinated system with breakdowns and rework/disposal of nonconforming items

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