An integrated inventory location routing problem considering CO2 emissions

Lerhlaly, Sanaa; Lebbar, Maria; Allaoui, Hamid; Ouazar, Driss; Afifi, Sohaib

doi:10.12988/ces.2016.512326

Cited by 11 publications

(7 citation statements)

References 20 publications

(26 reference statements)

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“…According to this demand, relevant inventory and transportation costs are obtained, making the model easier to establish and solve. Among the literature reviewed, there are 37 papers concerning deterministic needs [5,37,39,41,[43][44][45][46]49,50,59,63,65,[69][70][71][72][76][77][78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94][95].…”

Section: Classification Based On Demand Data Typesmentioning

confidence: 99%

Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method

et al. 2022

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A traditional logistics decision model mainly studies the location decision of logistics distribution centers, storage inventory management, vehicle scheduling, and transportation routes. The logistics location-inventory-routing problem (LIRP) is an integrated optimization of the three problems—a comprehensive optimization problem for the whole logistics system. This review paper uses the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method to review the literature on LIRP systematically. A total of 112 LIRP-related studies published between 2010 and 2021 are reviewed and classified based on 10 abstract and citation databases. The classification includes four aspects: problem characteristics, demand data types, model-based solutions, and application fields. From this systematic review, a few observations are recorded. First, the most popular problems among researchers are the multi-period multi-product problem, the multi-echelon single-link problem, and the multi-depot multi-retailer problem. Based on the objective function, the minimization of total supply chain cost is the primary concern of the LIRP literature. Researchers also favor other problem characteristics such as multi-objective programming, inventory control replenishment policy, and a homogeneous fleet of vehicles. We found that stochastic data are a common factor in an uncertain environment and have broad coverage. When dealing with the LIRP, heuristic and metaheuristic algorithms are the most widely used solution methodologies in the literature. In the application field of LIRP, the perishable products logistics network is mentioned in most applications. Finally, we discuss and emphasize the challenges of and recommendations for future work. This paper provides a systematic review of the literature on LIRP based on the PRISMA method, which contributes vital support and valuable information for researchers interested in LIRP.

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Section: Classification Based On Demand Data Typesmentioning

confidence: 99%

Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method

et al. 2022

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“…In addition, the pricing of low carbon operations is critical, and companies, therefore, should make marketing efforts to strengthen consumers' environmental preferences. Lerhlaly et al (2016) do also minimize total cost and co 2 emissions and consider a heterogeneous fleet of vehicles and multi-period decisions for an location routing inventory model for Hazmat. An LP model is presented and solved using the lexicographic weighting method with predefined priority orders, in which four weights are compared to determine the best co 2 emissions objective.…”

Section: Inventorymentioning

confidence: 99%

Bi- and multi-objective location routing problems: classification and literature review

Tadaros

Migdalas

2022

Oper Res Int J

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The facility location problem and the vehicle routing problem are highly interdependent and critical parts of any efficient and cost-effective supply chain. The location of facilities heavily affects the design of distribution routes between the facilities and various demand nodes. Within locational analysis, the location-routing problem is a mathematical optimization problem that considers the underlying issues of vehicle routing and simultaneously optimizes the location of facilities and the design of distribution routes. Since, in real-life applications, it is common that decision-makers encounter more than one, often conflicting objectives, the problem can be stated in term of multi-objective optimization. This paper reviews 80 journal articles published in the field of bi- and multi-objective location-routing problems between 2014 and 2020. Included papers are classified based on several factors covering model assumptions and characteristics, objectives, solution approaches, and application area. For each application area, individual papers are presented and discussed. The paper concludes with remarks and suggestions for future research.

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“…Customer K Lerhlaly et al (2016) analyses a realistic sample of two-level supply chain (distributor and consumer) with certain amount of demand and developed LIR model. One of the purposes of this research is route greenness and reduction of CO 2 diffusion by vehicle.…”

Section: Introductionmentioning

confidence: 99%

Developing an integrated decision making model in supply chain under demand uncertainty using genetic algorithm and network data envelopment analysis

Nakhjirkan

Rafiei

Kashan

2019

IJMOR

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Nowadays, organisations have recognised the importance of integrated decision making to improve supply chain performance. Since organisations cooperate with each other as a network, any ineffectiveness and inefficiency will be getting more highlighted and integration has become more important. This research describes a four echelon supply chain including supplier, producer, distributor and customer levels. The considered problem is a location routing inventory problem with uncertain demand. To validate integrated mathematical model several problems have been generated and solved using GAMS software. Results show solving time increases exponentially as problems dimension increases, which represents problem's complexity. Therefore, a heuristic genetic algorithm base on NDEA selection method is proposed. To evaluate proposed algorithm's effectiveness, generated problems have been solved by proposed method and three famous selection methods. Obtained results are compared by Wilcoxon test which represents the proposed algorithm's effectiveness.

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An integrated inventory location routing problem considering CO2 emissions

Cited by 11 publications

References 20 publications

Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method

Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method

Bi- and multi-objective location routing problems: classification and literature review

Developing an integrated decision making model in supply chain under demand uncertainty using genetic algorithm and network data envelopment analysis

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