Mathematical formulations and improvements for the multi-depot open vehicle routing problem

Lalla-Ruiz, Eduardo; Mes, Martijn

doi:10.1007/s11590-020-01594-z

Cited by 12 publications

(3 citation statements)

References 17 publications

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“…They compared the algorithm with several other algorithms and found that OVRP_SAICA performs better than all of them in solving the OVRP. Lalla-Ruiz and Mes ( 2021 ) proposed a two-index-based mathematical formulation for the MDOVRP. Also, they presented a memetic algorithm (MA) for solving the model.…”

Section: Literature Reviewmentioning

confidence: 99%

Green two-echelon closed and open location-routing problem: application of NSGA-II and MOGWO metaheuristic approaches

Heidari

Imani

Khalilzadeh

et al. 2022

Environ Dev Sustain

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Nowadays organizations outsource transportation of goods or services to reduce cost which leads to a particular type of problem called open location-routing. Also, each logistic organization possesses a limited number of specific vehicles that may not be enough in certain circumstances. This issue indicates the importance of simultaneously considering both open and closed routs. On the other hand, the growing concerns about the detrimental environmental impacts of human activities reveal the necessity of paying attention to environmental issues in logistics. In this study, a bi-objective mathematical programming model is proposed for two-echelon close and open location-routing problem (2E-COLRP) including two echelons of factories, depots and customers to minimize costs and CO 2 emissions. The proposed model finds the optimal routs, optimal number of vehicles and facilities as well as the locations of facilities. The augmented epsilon constraint method is used as an exact method to solve the small-sized problems. Due to complexity of model, two metaheuristic algorithms named MOGWO and NSGA-II are utilized to tackle the problems. The efficiency of two aforementioned algorithms is evaluated in terms of several indices considering 22 problem instances with various sizes. The results show that MOGWO performs better than NSGA-II.

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Section: Literature Reviewmentioning

confidence: 99%

Green two-echelon closed and open location-routing problem: application of NSGA-II and MOGWO metaheuristic approaches

Heidari

Imani

Khalilzadeh

et al. 2022

Environ Dev Sustain

View full text Add to dashboard Cite

show abstract

“…Regarding the variant of the MDVRP that considers open routes (MDVORP) problem was introduced in the literature by Tarantilis and Kiranoudis (2002) to tackle a distribution problem of fresh meat, considering a homogeneous fleet of vehicles. Since then, relevant studies such as (Lalla-Ruiz et al, 2016;Lalla-Ruiz & Mes, 2020;Liu et al, 2014;Soto et al, 2017) proposed mathematical formulations and efficient metaheuristic algorithms to handle this problem.…”

Section: Literature Reviewmentioning

confidence: 99%

The multi-depot open location routing problem with a heterogeneous fixed fleet

Nucamendi-Guillén

Padilla

Olivares-Benítez

et al. 2021

Expert Systems with Applications

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This paper introduces the multi-depot open location routing problem (MD-OLRP) with a heterogeneous fixed fleet. The problem is inspired by the collection problem of a company which collects raw materials from different suppliers coordinating several carriers. Each carrier has a heterogeneous fixed fleet. Moreover, there is a fixed cost for contracting each vehicle and a variable cost associated with the distance traveled. The empty haul return to the vehicles depot is not considered in the cost. The raw materials collected are delivered to a single delivery point. The problem is modeled as a Mixed Integer Linear Program (MILP) that minimizes the total cost, selecting the carriers to be contracted, the vehicles to be used from each contracted carrier and the collection routes. For small instances, the model can be solved to optimality. However, approximate procedures are necessary to handle larger instances. In this sense, in the present work we propose an intelligent metaheuristic which incorporates problem specific knowledge to solve it. The computational results show that the solution method is computationally efficient and provides high quality solutions. In particular, the new solution obtained for the case of study generates savings of 30.86% to the company.The main contributions of the paper are the new problem statement that was not found in the literature, its association to the real problem of a company and the intelligent metaheuristic proposed to solve it. Additional experimentation used the model proposed to solve a simpler problem obtaining new best solutions compared to those reported in the recent literature.

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“…The battery manufacturing industry is one of the application areas for VRP (as a two-echelon problem), and in [ 41 ], the green transportation problem for this area is considered a two-echelon problem. At the first echelon, the green transportation with inventory problem is discussed, and at the second echelon, the simultaneous pickup and delivery of capacitated multidepot (distribution and collection center) heterogeneous green vehicle routing problem (MDHVRPSPD) is the main focus (heterogeneous vehicles for the multidepot routing problem are discussed in [ 34 ] with a definition of open location (MD-OLRP), and in [ 26 ], the multidepot open vehicle routing problem (MDOVRP) is analyzed with state-of-the-art formulations). Three objectives are selected and integrated in the problem: carrying cost, transportation cost and carbon emission cost (as a single-objective problem).…”

Section: Introductionmentioning

confidence: 99%

Multiobjective problem modeling of the capacitated vehicle routing problem with urgency in a pandemic period

Altınöz

2022

Neural Comput & Applic

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This research is based on the capacitated vehicle routing problem with urgency where each vertex corresponds to a medical facility with a urgency level and the traveling vehicle could be contaminated. This contamination is defined as the infectiousness rate, which is defined for each vertex and each vehicle. At each visited vertex, this rate for the vehicle will be increased. Therefore time-total distance it is desired to react to vertex as fast as possible- and infectiousness rate are main issues in the problem. This problem is solved with multiobjective optimization algorithms in this research. As a multiobjective problem, two objectives are defined for this model: the time and the infectiousness, and will be solved using multiobjective optimization algorithms which are nondominated sorting genetic algorithm (NSGAII), grid-based evolutionary algorithm GrEA, hypervolume estimation algorithm HypE, strength Pareto evolutionary algorithm shift-based density estimation SPEA2-SDE, and reference points-based evolutionary algorithm.

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Mathematical formulations and improvements for the multi-depot open vehicle routing problem

Cited by 12 publications

References 17 publications

Green two-echelon closed and open location-routing problem: application of NSGA-II and MOGWO metaheuristic approaches

Green two-echelon closed and open location-routing problem: application of NSGA-II and MOGWO metaheuristic approaches

The multi-depot open location routing problem with a heterogeneous fixed fleet

Multiobjective problem modeling of the capacitated vehicle routing problem with urgency in a pandemic period

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