Multi-period green reverse logistics network design: An improved Benders-decomposition-based heuristic approach

Kumar, Akhilesh; Kumar, Akhilesh; Choudhary, Anshul; Cheng, T C Edwin

doi:10.1016/j.ejor.2022.03.014

Cited by 45 publications

(15 citation statements)

References 104 publications

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“…Then, stepsize is updated by using q j+1 per (21) and is used to update multipliers until the next time it is updated to q j+2 when the "multiplier-divergence-detection" problem is infeasible again, and the process repeats. Per (21), SLBLR requires hyperparameter ζ , yet, it is set before the algorithm is run and subsequently is not adjusted (see "Numerical testing" section for empirical demonstration of the robustness of the method with respect to the choice of hyperparameter ζ).…”

Section: Corollary 1 If Thenmentioning

confidence: 99%

“…Within the SLBLR method, the equation ( 15) is used to detect divergence, and ζ = 1 2 is used to set stepsizes within (21). In essence, only one hyperparameter was required, which has a quite simple explanation -"when the stepsize is 'too large, ' cut the stepsize in half. "…”

Section: Demonstration Of Convergence Of Multipliers Based On a Small...mentioning

confidence: 99%

“…Mixed-Integer Linear Programming (MILP) plays an important role across a range of scientific disciplines such as mathematics, operations research, engineering, and computer science as well as within a range of areas of strategic importance to society such as biology 1,2 , healthcare 3,4 , humanitarian applications [5][6][7][8] , manufacturing [9][10][11][12] , pharmacy [13][14][15][16] , power and energy systems [17][18][19] , transportation and logistics 20,21 and many others.…”

mentioning

confidence: 99%

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Surrogate “Level-Based” Lagrangian Relaxation for mixed-integer linear programming

Bragin

Tucker

2022

Sci Rep

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Mixed-Integer Linear Programming (MILP) plays an important role across a range of scientific disciplines and within areas of strategic importance to society. The MILP problems, however, suffer from combinatorial complexity. Because of integer decision variables, as the problem size increases, the number of possible solutions increases super-linearly thereby leading to a drastic increase in the computational effort. To efficiently solve MILP problems, a “price-based” decomposition and coordination approach is developed to exploit 1. the super-linear reduction of complexity upon the decomposition and 2. the geometric convergence potential inherent to Polyak’s stepsizing formula for the fastest coordination possible to obtain near-optimal solutions in a computationally efficient manner. Unlike all previous methods to set stepsizes heuristically by adjusting hyperparameters, the key novel way to obtain stepsizes is purely decision-based: a novel “auxiliary” constraint satisfaction problem is solved, from which the appropriate stepsizes are inferred. Testing results for large-scale Generalized Assignment Problems demonstrate that for the majority of instances, certifiably optimal solutions are obtained. For stochastic job-shop scheduling as well as for pharmaceutical scheduling, computational results demonstrate the two orders of magnitude speedup as compared to Branch-and-Cut. The new method has a major impact on the efficient resolution of complex Mixed-Integer Programming problems arising within a variety of scientific fields.

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Section: Corollary 1 If Thenmentioning

confidence: 99%

Section: Demonstration Of Convergence Of Multipliers Based On a Small...mentioning

confidence: 99%

mentioning

confidence: 99%

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Surrogate “Level-Based” Lagrangian Relaxation for mixed-integer linear programming

Bragin

Tucker

2022

Sci Rep

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“…Future studies can address the use of lateral collaboration. Given the high computational complexity of the presented mathematical model resulting from a combination of binary and continuous variables, the development of new exact solution methods, such as the benders decomposition algorithm (Reddy et al, 2022 ) or new meta-heuristic algorithms (Hashim et al, 2022 ; Tanhaeean et al, 2022 ) for the presented model can be an attractive research topic.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

A robust, sustainable, resilient, and responsive model for forward/reverse logistics network design with a new approach based on horizontal collaboration

Saffari

Abbasi

Gheidar-Kheljani

2023

Environ Dev Sustain

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Optimizing the strategic and tactical decisions regarding sustainability and resilience is important because they affect the performance of the supply chain over a long period. This study proposes a new multi-objective model for resilient, sustainable, and responsive forward/reverse logistics network design considering cost, social responsibility, CO 2 emission, water consumption, responsiveness time, and collaboration risk. The most significant impacts on costs are identified using the design of experiments, and a robust optimization method is applied to deal with operational risk. In addition, horizontal collaboration for the first time as a quantitative model is suggested to deal with the disruption risk. Also, a multi-objective solving algorithm with a new aggregation model is developed, and the efficiency of the proposed solution method is shown. The analysis of results based on the iron and steel industries shows the efficiency of resilience strategies and the improvement of costs, sustainability and responsiveness indicators. Also, the findings demonstrate that collaboration has a higher performance than fortification. Finally, managers and supply chain decision-makers are provided with managerial implications to make more effective decisions about the supply chain network design, technology selection, supply chain sustainability, and collaborators selection, using the presented results.

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“…Along with this trend, people have begun to pay attention to environmental protection and energy conservation in the logistics and warehousing industry, and gradually accepted the concept of green warehousing [11][12][13][14][15]. Implementing green warehousing management can reduce the environmental pollution caused by warehousing while ensuring the quality and quantity of the stored goods, and improve the various problems of regular logistics storage space such as heavy environmental pollution, high energy consumption, large cargo loss, poor thermal environment and high transportation costs [16][17][18][19][20][21]. Among these problems, high temperature in summer is the most prominent one.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Heat and Moisture Transfer and Thermal Comfort in Green Logistics Storage Space

Wang¹,

Lu²

2022

IJHT

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Regular logistics storage spaces suffer a very high temperature during summer. To build a green logistics storage space, it is truly necessary to optimize the thermal environment in summer. At present, there are few related studies on the energy consumption, thermal environment and human comfort of green logistics storage spaces. Therefore, this paper analyzes the heat and moisture transfer in and studies the impacts of the thermal environment of green logistics storage space. Based on the survey results, a coupled heat-moisture transfer model of green logistics storage space was constructed, which consists of three parts - the envelope structure, the hot and humid indoor environment, and the heating, ventilation and air conditioning (HVAC) system. Based on the idea of linear regression, a model was established to predict human body’s subjective thermal sensation in green logistics storage space. The experiment showed the analysis results of heat and moisture transfer and thermal comfort in green logistics storage space, and verified the effectiveness of the proposed model.

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Multi-period green reverse logistics network design: An improved Benders-decomposition-based heuristic approach

Cited by 45 publications

References 104 publications

Surrogate “Level-Based” Lagrangian Relaxation for mixed-integer linear programming

Surrogate “Level-Based” Lagrangian Relaxation for mixed-integer linear programming

A robust, sustainable, resilient, and responsive model for forward/reverse logistics network design with a new approach based on horizontal collaboration

Analysis of Heat and Moisture Transfer and Thermal Comfort in Green Logistics Storage Space

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