A multi-objective closed-loop supply chain network design problem under parameter uncertainty: comparison of exact methods

Abdolazimi, Omid; Bahrami, Farzad; Shishebori, Davood; Ardakani, Majid Alimohammadi

doi:10.1007/s10668-021-01883-2

Cited by 10 publications

(3 citation statements)

References 56 publications

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“…Among the articles in this field selected for this study, Refs. [144][145][146][147][148][149][150][151] applied uncertainty method based on uncertainty theory. For example, Goltsos et al [144] and Peng et al [145] conducted review studies of the literature related to CLSC and uncertainty.…”

Section: Study Of Hazardous Materials Transportation To Minimize Risk...mentioning

confidence: 99%

Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review

et al. 2023

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In recent years, there have been frequent cases of impact on the stable development of supply chain economy caused by uncertain events such as COVID-19 and extreme weather events. The creation, management, and impact coping techniques of the supply chain economy now face wholly novel requirements as a result of the escalating level of global uncertainty. Although a significant literature applies uncertainty analysis and optimization modeling (UAO) to study supply chain management (SCM) under uncertainty, there is a lack of systematic literature review and research classification. Therefore, in this paper, 121 articles published in 44 international academic journals between 2015 and 2022 are extracted from the Web of Science database and reviewed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Bibliometric analysis and CiteSpace software are used to identify current developments in the field and to summarize research characteristics and hot topics. The selected published articles are classified and analyzed by author name, year of publication, application area, country, research purposes, modeling methods, research gaps and contributions, research results, and journals to comprehensively review and evaluate the SCM in the application of UAO. We find that UAO is widely used in SCM under uncertainty, especially in the field of decision-making, where it is common practice to abstractly model the decision problem to obtain scientific decision results. This study hopes to provide an important and valuable reference for future research on SCM under uncertainty. Future research could combine uncertainty theory with supply chain management segments (e.g., emergency management, resilience management, and security management), behavioral factors, big data technologies, artificial intelligence, etc.

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Section: Study Of Hazardous Materials Transportation To Minimize Risk...mentioning

confidence: 99%

Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review

et al. 2023

View full text Add to dashboard Cite

show abstract

“…An uncertain multi-objective MILP model of the CLSC network design was studied to minimize the total costs, maximize the on-time delivery of the products purchased from suppliers, and maximize the quality of the produced products on the forward chain that can be recovered in the reverse supply chain using an SRO method [45]. Gholizadeh et al [46] proposed a bi-objective model to minimize the environmental impact and maximize profit for a dairy CLSC using a heuristic approach and robust optimization scenario-based.…”

Section: Uncertain Multi-objective Clsc Networkmentioning

confidence: 99%

Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration

et al. 2022

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In this study, we propose a robust bi-objective optimization model of the green closed-loop supply chain network considering presorting, a heterogeneous transportation system, and carbon emissions. The proposed model is an uncertain bi-objective mixed-integer linear optimization model that maximizes profit and minimizes carbon emissions by considering uncertain costs, selling price, and carbon emissions. The robust optimization approach is implemented using the combined interval and polyhedral, “Interval+ Polyhedral,” uncertainty set to develop the robust counterpart of the proposed model. Robust Pareto optimal solutions are obtained using a lexicographic weighted Tchebycheff optimization approach of the bi-objective model. Intensive computational experiments are conducted and a robust Pareto optimal front is obtained with a probability guarantee that the constraints containing uncertain parameters are not violated (constraint satisfaction).

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“…In the case of discrete facility location, a limited number of locations can be used as candidates for a new facility. The simplest way to deal with this issue in network design is to deploy facilities in such a way as to minimize the total distances or the costs of meeting customer demands [7,28]. In the literature, this task is generally known as facility location, regardless of capacity.…”

Section: Literature Reviewmentioning

confidence: 99%

An integrated dynamic model to locate a competitive closed-loop supply chain facility under conditions of uncertainty: A case study of the auto parts industry

Ardekani¹,

Naeini

2022

RAIRO-Oper. Res.

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With the expansion of competitive markets, supply chain management has become one of the critical issues facing businesses. One of the advantages of sustainable competition for companies is to make supply chain activities more efficient and effective. This paper aims at an integrated closed-loop supply chain (CLSC) problem which is multi-objective, multi-product, multi-period, and multi-level with limited capacities and uncertain conditions of demand and return products. The proposed supply chain network consists of five levels in the forward flow. There are five centers in the backward flow as well. The purpose of this network is to determine the optimal number and location of facilities required in each period and the optimal amount of the transfer flow of products or raw materials through different transportation modes between facilities. In this proposed model, three objective functions are taken into consideration. The first one minimizes all the costs. The second objective function maximizes the quality of products. The third objective function seeks to minimize the sum of deviations from the ideal score of the principal component of each supplier. The data of this research are taken from Pishro Diesel Company. To solve the proposed problem, several methods and algorithms have been used, including unscaled goal programming, boundary objectives, three single-objective meta-heuristic algorithms (PSO, RDA, and TGA), and multi-objective meta-heuristic algorithm (MOGA-II). As the results show, considering products and returned parts in products, a simultaneous practice of forward and reverse supply chains leads to better product quality, less damage to the environment, and lower costs for customers.

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A multi-objective closed-loop supply chain network design problem under parameter uncertainty: comparison of exact methods

Cited by 10 publications

References 56 publications

Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review

Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review

Robust Optimization for a Bi-Objective Green Closed-Loop Supply Chain with Heterogeneous Transportation System and Presorting Consideration

An integrated dynamic model to locate a competitive closed-loop supply chain facility under conditions of uncertainty: A case study of the auto parts industry

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