A genetic algorithm-Taguchi based approach to inventory routing problem of a single perishable product with transshipment

Azadeh, A.; Elahi, Saeed; Farahani, Mehdi Hosseinabadi; Nasirian, B.

doi:10.1016/j.cie.2016.12.019

Cited by 96 publications

(51 citation statements)

References 46 publications

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“…The genetic simulated annealing algorithm (GASA) was developed in order to solve the problem more efficiently. Scholars have efficiently demonstrated that the genetic algorithm has gradually developed to be applied in the IRP problem [36][37][38]. However, the genetic algorithm still has the disadvantage of precocity and its local-search ability is weak.…”

Section: Environmentally Conscious Inventory Routing Modelsmentioning

confidence: 99%

Optimization of Integrated Inventory Routing Problem for Cold Chain Logistics Considering Carbon Footprint and Carbon Regulations

Yang

Qin

2019

Sustainability

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This paper studies the optimization of cold chain integrated inventory routing problem while considering carbon emissions. First, the carbon footprint in inventory and transportation process for cold chain logistics is accurately identified and quantified. Secondly, based on the carbon regulations, which are carbon cap, carbon cap and offset, carbon cap and trade, and carbon tax regulations, four green cold chain inventory routing optimization models that minimize the total cost are constructed, respectively. Subsequently, a genetic simulated annealing algorithm (GASA) is developed in order to efficiently solve the models, which combines the advantages of the two algorithms. The effectiveness of the algorithm and the models is verified by numerical comparison experiments. Further, a set of numerical experiments is conducted to examine in detail the effectiveness of each regulation with the change of cap, carbon price, and unit fuel price in order to investigate the difference of these regulations’ impacts on the cold chain logistics. The research results show that (a) the cap and price plays a relatively important role, for their value setting may even lead to the invalidation of the regulations and the development of the enterprises; (b) carbon cap and carbon tax regulations are more powerful when compared to the other two regulations, which reduce more carbon emissions, but also pose more challenge to the enterprises’ economic development; (c) overall, cap and trade regulation is better than cap and offset regulation, because, when the cap is not sufficient, the two regulations are almost as good, but when the cap is sufficient, the offset policy is invalid; and, (d) unlike the traditional logistics, the increase of unit fuel price will not reduce carbon emissions. Several practical managerial implications for government and enterprises are also provided based on research results.

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Section: Environmentally Conscious Inventory Routing Modelsmentioning

confidence: 99%

Optimization of Integrated Inventory Routing Problem for Cold Chain Logistics Considering Carbon Footprint and Carbon Regulations

Yang

Qin

2019

Sustainability

View full text Add to dashboard Cite

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“…The authors propose a three-phase heuristic, which decomposes the decision process into i) replenishment plans using a Lagrangian-based method, ii) delivery sequences for the vehicles using a simple procedure, and iii) planning and routing decisions using a mixed-integer linear programming model. More recently, other approximate solution approaches have been designed for the IRP; for example, a genetic algorithm (GA) approach for the IRP of a single perishable product by Azadeh et al (2017), a hybrid randomized variable neighborhood descent for the multi-vehicle, multi-product and multi-period IRP by Peres et al (2017), a GA for location-inventoryrouting model for perishable products by Hiassat et al (2017), a discrete invasive weed optimization and a GA for the IRP for a single product with allowed backorders by Jahangir et al (2019), to name but a few. In recent years, environmental concerns have also made their way into the IRP and several works have been published.…”

Section: Introductionmentioning

confidence: 99%

A Genetic Algorithm for a Multi-Product Distribution Problem

Cretu¹,

Fontes²,

Homayouni³

2019

IJQR

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This paper addresses a distribution problem involving a set of different products that need to be distributed among a set of geographically disperse retailers and transported from the single warehouse to the aforementioned retailers. The distribution and transportation are made in order to satisfy retailers' demand while satisfying storage limits at both the warehouse and the retailers, transportation limits between the warehouse and the retailers, and other operational constraints. This problem is combinatorial in nature as it involves the assignment of a discrete finite set of objects, while satisfying a given set of conditions. Hence, we propose a genetic algorithm that is capable of finding good quality solutions. The genetic algorithm proposed is used to a real case study involving the distribution of eight products among 108 retailers from a single warehouse. The results obtained improve on those of company's current practice by achieving a cost reduction of about 13%.

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“…IRP consists in satisfying the demand of customers that are geographically spread over a planning horizon while satisfying inventory levels constraints and vehicle capacity constraints (Azadeh et al, 2017). As an extension of the classic vehicle routing problem, IRP is a difficult optimization problem because of the coordination of the various related decisions.…”

Section: Introductionmentioning

confidence: 99%

Dynamic inventory routing problem: Policies considering network disruptions

2018

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In this paper, we introduce an inventory routing problem with network disruptions. In this problem, not only decisions on inventory levels and vehicle routing are made simultaneously, but also, we consider disruptions over the networks in which a number of arcs are vulnerable to these disruptions, leading to an increase in travel times. We develop a dynamic programming approach to deal with this situation, and we also evaluate some policies adapting well-known instances from the literature.

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A genetic algorithm-Taguchi based approach to inventory routing problem of a single perishable product with transshipment

Cited by 96 publications

References 46 publications

Optimization of Integrated Inventory Routing Problem for Cold Chain Logistics Considering Carbon Footprint and Carbon Regulations

Optimization of Integrated Inventory Routing Problem for Cold Chain Logistics Considering Carbon Footprint and Carbon Regulations

A Genetic Algorithm for a Multi-Product Distribution Problem

Dynamic inventory routing problem: Policies considering network disruptions

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