Effect of raw material substitution on the facility location decision under a carbon tax policy

Mechouar, Youcef; Hovelaque, Vincent; Gaigné, Carl

doi:10.1016/j.ejtl.2021.100061

Cited by 6 publications

(2 citation statements)

References 36 publications

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“…Yin [ 30 ] studied the p-hub low carbon location problem under uncertain demand using robust optimization method to convert carbon emissions into carbon cost and solved it using Cplex software. Wang [ 31 ] studied the supply chain-site-inventory problem under uncertain demand utilizing a stochastic programming approach, converting carbon emissions into carbon costs, and solving it using metaheuristic algorithms; Mechouar [ 32 ] studied the impact of carbon tax policies on siting options under demand determination, converted carbon emissions into carbon costs to construct a siting model with the minimum total cost, and solved it using the Generalized Reduced Gradient (GRG) algorithm. Wang [ 33 ] used a stochastic programming approach to consider the supply chain location problem under uncertain demand, developed a multi-objective model for logistics costs and carbon emissions, and solved the Pareto solution set utilizing a metaheuristic algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

Aptenodytes forsteri optimization algorithm for low-carbon logistics network under demand uncertainty

Zhu,

Fan,

Yin

2024

PLoS ONE

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As China’s "double carbon" goal continues to advance, logistics as a key area of carbon emissions and low-carbon logistics center site selection are key links in the process. However, existing studies on logistics center location often ignore the impact of demand uncertainty, which leads to a waste of resources in the planning and construction processes. We take logistics cost and carbon emission as the objectives, and the multi-objective site selection model established based on stochastic programming theory takes demand uncertainty as a stochastic constraint. We transform the stochastic constraint model into a 0–1 mixed integer multi-objective planning model by utilizing the idea of equivalence transformation. The Aptenodytes Forsteri Optimization (AFO) algorithm is combined with the Ideal Point Method to solve the model, and the algorithm is compared with the Particle Swarm Optimization (PSO), Differential Evolutionary (DE), Tabu Search (TS), Sparrow Search (SS) algorithms, and the exact solver Linear Interactive and General Optimizer (LINGO). The examples verify the validity of the models and algorithms, with an average reduction of 6.2% and 3.6% in logistics costs and carbon emissions in the case of demand determination, and at the confidence level of 0.9 under demand uncertainty, both logistics costs and carbon emissions are decreased to varying degrees. This study provides a new research idea for the low-carbon logistics location problem under demand uncertainty, which helps to promote the transformation of the logistics industry to low-carbon and high-efficiency.

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Section: Literature Reviewmentioning

confidence: 99%

Aptenodytes forsteri optimization algorithm for low-carbon logistics network under demand uncertainty

Zhu,

Fan,

Yin

2024

PLoS ONE

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“…The key sources of expenses for broiler wholesalers are generally classified as direct and indirect costs, according to the survey results on processing costs in the broiler sector(Korea Agro-Fisheries Trade Corporation, 2022). Transport expenditures accounted for the greatest proportion of the former, while labor and utility fees accounted for the greatest proportion of the latter.3 The underlying idea is that a rise in freight transport costs may reduce demand for transportation, leading to reduced production amounts(Mechouar et al, 2022). As a result, it may reduce the storage demand for manufactured products in the refrigeration system, diminishing electricity demand.4 Previous studies have consistently found that there is a symmetric price transmission(Hwang & Park., 2013;Lim & Cho, 2012;Kang, 2011), which is exhibited under a competitive market, from farm to wholesale markets in the South Korean broiler supply chain.…”

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Market power and cost‐efficiency effects: Broiler packing industry in South Korea

Kang

Ahn

2023

Agribusiness

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The effects of rising concentration on markups in the meatpacking industry have sparked ongoing global debate. In this vein, our study aimed to decompose these effects into two opposing components: market power and cost‐efficiency effects. We applied our model to the broiler packing industry in South Korea. Our findings indicate that cost‐efficiency effects decreased sharply from 74.642 in 2017 to ‐145.860 in 2021, while market power effects remained stable during the study period. We found that the decrease in cost‐efficiency effects has begun to counteract the market power effects, which can largely be attributed to profix‐maximizing behavior of broiler packers in response to the bird flu outbreak. Moreover, we highlighted that non‐material price changes were a significant source of the reduction in cost‐efficiency effects, which underscores the necessity of policy efforts to manage factor market situations in order to mitigate the negative consequences of market concentration. [EconLit Citations: D43, L11, Q13].

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Iterated Local Search for the Facility Location Problem with Limited Choice Rule

García-Galán,

Herrán,

Colmenar

2024

Lecture Notes in Computer Science

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Effect of raw material substitution on the facility location decision under a carbon tax policy

Cited by 6 publications

References 36 publications

Aptenodytes forsteri optimization algorithm for low-carbon logistics network under demand uncertainty

Aptenodytes forsteri optimization algorithm for low-carbon logistics network under demand uncertainty

Market power and cost‐efficiency effects: Broiler packing industry in South Korea

Iterated Local Search for the Facility Location Problem with Limited Choice Rule

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