Supply network design with uncertain demand: Computational cooperative game theory approach using distributed parallel programming

Tokgoz, Emre; Mahjoub, S.; Taeib, Tarik El; Bachkar, Khalid

doi:10.1016/j.cie.2022.108011

Cited by 6 publications

(6 citation statements)

References 51 publications

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“…The increasing cost of freight has a growing impact on site selection, and decision-makers will take different measures to reduce transportation costs. When the freight cost is between [ 6 , 12 ], decision-makers will adjust the distribution scheme to shorten the transportation distance and reduce transportation costs. At this time, carbon emissions fluctuate less.…”

Section: Case Studymentioning

confidence: 99%

“…Tokgo ¨z [6] normal distributions Shahabi [12] normal distributions Saberi [7] normal distributions Wang [13] Lognormal distribution…”

Section: Probability Distribution Paper Probability Distributionmentioning

confidence: 99%

“…A3. The demand for goods at each demand point is independent of each other and follows a normal distribution [5][6][7][8][9][10][11][12][13][14][15].…”

Section: Plos Onementioning

confidence: 99%

“…For the uncertainty of cargo demand, this paper uses the stochastic programming idea to transform the uncertain stochastic programming into a meaningful opportunity-constrained model. Since the stochastic programming approach is based on the important assumption that the probability distributions of uncertain parameters must be known or estimated, by reviewing and summarizing the references [5][6][7][8][9][10][11][12][13][14][15] related to supply chain demand uncertainty, as shown in Table 1, the relevant scholars assume the distribution of cargo demand as normal when studying cargo demand uncertainty, so this paper assumes the cargo demand as normal with reference to the previous studies.…”

Section: Introductionmentioning

confidence: 99%

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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: Case Studymentioning

confidence: 99%

“…Tokgo ¨z [6] normal distributions Shahabi [12] normal distributions Saberi [7] normal distributions Wang [13] Lognormal distribution…”

Section: Probability Distribution Paper Probability Distributionmentioning

confidence: 99%

“…A3. The demand for goods at each demand point is independent of each other and follows a normal distribution [5][6][7][8][9][10][11][12][13][14][15].…”

Section: Plos Onementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Zhu,

Fan,

Yin

2024

PLoS ONE

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“…Maihami and Ghalehkhondabi (2022) use nonlinear optimization to examine the pricing and environmental investment of supply chains. Tokgöz et al . (2022) explore the design of supply networks under uncertain demands.…”

Section: Literature Reviewmentioning

confidence: 99%

Operational decisions of low-carbon supply chains with triple bottom line under carbon tax policy

2023

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PurposeUnder the carbon tax policy, the authors examine the operational decisions of the low-carbon supply chain with the triple bottom line.Design/methodology/approachThis paper uses the Stackelberg game theory to obtain the optimal wholesale prices, retail prices, sales quantities and carbon emissions in different cases, and investigates the effect of the carbon tax policy.FindingsThis study’s main results are as follows: (1) the optimal retail price of the centralized supply chain is the lowest, while that of the decentralized supply chain where the manufacturer undertakes the carbon emission reduction (CER) responsibility and the corporate social responsibility (CSR) is the highest under certain conditions. (2) The sales quantity when the retailer undertakes the CER responsibility and the CSR is the largest. (3) The supply chain obtains the highest profits when the retailer undertakes the CER responsibility and the CSR. (4) The environmental performance impact decreases with the carbon tax.Practical implicationsThe results of this study can provide decision-making suggestions for low-carbon supply chains. Besides, this paper provides implications for the government to promote the low-carbon market.Originality/valueMost of the existing studies only consider economic responsibility and social responsibility or only consider economic responsibility and environmental responsibility. This paper is the first study that examines the operational decisions of low-carbon supply chains with the triple bottom line under the carbon tax policy.

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Designing a sustainable reverse logistics network for used cell phones based on offline and online trading systems

Chen,

Liu,

Han

2024

Journal of Environmental Management

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Supply network design with uncertain demand: Computational cooperative game theory approach using distributed parallel programming

Cited by 6 publications

References 51 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

Operational decisions of low-carbon supply chains with triple bottom line under carbon tax policy

Designing a sustainable reverse logistics network for used cell phones based on offline and online trading systems

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