A bi-level programming model for sustainable supply chain network design that considers incentives for using cleaner technologies

Chalmardi, Mazyar Kaboli; Camacho‐Vallejo, José‐Fernando

doi:10.1016/j.jclepro.2018.12.197

Cited by 83 publications

(37 citation statements)

References 30 publications

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“…They applied a fuzzy goal programming method to reduce the related costs and environmental effects of the system concurrently. Chalmardi and Camacho-Vallejo [25] developed a SCND problem and considered the social and environmental aspects alongside with economical objectives in the problem. In the proposed model the government plays the role of leader and the manager of the company plays the role of follower and a simulation annealing (SA) based algorithm is applied to solve the problem.…”

Section: Lean Agility Sustainability and Disruption Risk In The Supmentioning

confidence: 99%

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A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

2020

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In the current situation, taking into consideration the environmental and social issues are related with the production and distribution of products in supply chain systems, due to the global concerns related with emitting lots of greenhouse gases within the manufacturing process and overlooking the major needs of public. This paper proposes a new multi objective model in the area of closed loop supply chain problem integrated with lot sizing by considering lean, agility and sustainability factors simultaneously. Next, a robust possibilistic programming approach is applied to handle the uncertainty of the model. To increase the responsiveness of the system, a fuzzy c-means clustering method is applied to select the potential locations based on the proximity to local customers. In the following, a new hybrid metaheuristic algorithm is developed to deal with large size problems efficiency and to assess the impact of using a single-based initial solution as the income for the second phase of the proposed hybrid algorithm. To ensure about the effectiveness of the proposed algorithm, another well-known metaheuristic algorithm is developed too. The results reached from experiments on different test problems approve the superiority of the hybrid metaheuristic algorithm to find better solutions.

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Section: Lean Agility Sustainability and Disruption Risk In The Supmentioning

confidence: 99%

“…24is associated with flow protection and indicates that when a vehicle visits a place, the vehicle should leave that place within an equal time period. The constraint (25) states that maximum one PDC can exists in a route. The constraint (26) describes that a retailor should be allotted to a PDC if there is a connection between them by vehicle.…”

mentioning

confidence: 99%

A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

2020

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“…To deal with the complexity of such NP-hard problems, evolutionary algorithms (EA) have attracted much attention. Among EAs, genetic algorithm (GA) has been widely investigated because of its capability to efficiently solve intricate problems within a reasonable amount of time in several fields, like routing-based problems, [75][76][77]. A two-stage GA has been presented by Fazayeli et al [76] to cope with a location-routing problem with time windows and fuzzy demands.…”

Section: Solution Approaches For Bilevel Modelsmentioning

confidence: 99%

Joint Optimization of a Bilevel Logistics Network and an Arc Interdiction Location-routing Problem

Babaeinesami

Tohidi

Seyedaliakbar

2020

IJE

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There is a high interest in optimization of transportation and logistics networks due to its high impact on the economic performance of supply chain networks. This paper presents a bilevel mixed-integer programming model as well as a solution method to manage distribution process in a logistic network, where two decision makers, called distributor and interdictor, make efforts to achieve their contradictory targets. This problem, known as arc interdiction location-routing problem (AI-LRP), is in fact a new, extended version of the classical LRP. The distributor strives to deliver goods to customers with minimal risk and cost, while the interdictor, by contrast, endeavors to disrupt products flow through a few critical arcs. AI-LRP has wide applications in reality, including distribution of particular goods like money, precious metals, hazardous materials, and prisoners that may need security measures. The interplay between two decision makers is formulated as a bilevel model. To solve the model, a novel genetic algorithm (NGA) is devised in which the density ordered heuristic of the knapsack problem is applied to generate an initial population of solutions. Computational results illustrate that NGA outperforms a commercial solver in terms of computational time and quality of solutions.

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“…The increased attention to the environmental factors encourages some researchers to address the environmental factor along with the traditional economic factor. Some researchers developed bi-objective models with economic-environmental objective functions [16,21,30,31,45,46]. Their models aim to minimize the environmental impacts through minimizing CO2 emissions released from production or transportation processes.…”

Section: Economic and Environmental Objective Functionsmentioning

confidence: 99%

“…Whereas, HGA is faster than HHS. Chalmardi and Camacho-Vallejo [16] and Eskandari-Khanghahi et al [3] proposed an algorithm depending on the simulated annealing (SA) metaheuristic method. The performance of the SA algorithm and that of the harmony search (HS) algorithm are compared.…”

Section: Field Of Applicationsmentioning

confidence: 99%

Sustainable Supply Chain Design for Perishable Products: A Literature Review

Nabil

Afia

Shihata

2020

JES. Journal of Engineering Sciences

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A bi-level programming model for sustainable supply chain network design that considers incentives for using cleaner technologies

Cited by 83 publications

References 30 publications

A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

A hybrid metaheuristic algorithm for a data driven leagile sustainable closed-loop supply chain model under disruption risks

Joint Optimization of a Bilevel Logistics Network and an Arc Interdiction Location-routing Problem

Sustainable Supply Chain Design for Perishable Products: A Literature Review

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