Robust aggregate production planning in a green supply chain under uncertainty considering reverse logistics: a case study

Entezaminia, Arezoo; Heidari, Mahdi; Rahmani, Donya

doi:10.1007/s00170-016-9459-6

Cited by 49 publications

(29 citation statements)

References 43 publications

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“…e most commonly and extensively stated sources of uncertainty are connected to the customers' demand, process, and supply that have huge effects on the decisionmaking process. To incorporate uncertainty in an optimisation model, several approaches can be addressed such as stochastic programming methods [17], fuzzy programming [10], and robust optimisation techniques [18]. One of the most widely used formulations for decisionmaking under uncertainty is stochastic programming with recourse.…”

Section: Related Literaturementioning

confidence: 99%

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An Integrated Production-Distribution Planning Problem under Demand and Production Capacity Uncertainties: New Formulation and Case Study

Abid

Ayadi

Masmoudi

2020

Mathematical Problems in Engineering

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In this study, we propose to solve a biobjective tactical integrated production-distribution planning problem for a multisite, multiperiod, multiproduct, sea-air intermodal supply chain network under uncertainties. Two random parameters are considered simultaneously: product replenishment orders and production capacity, which are modelled via a finite set of scenarios, using a two-stage stochastic approach. A corresponding mathematical model is developed, coded, and solved using the LINGO 18.0 software optimisation tool. This model aims to simultaneously minimise the total costs of production in both regular and overtime, inventory, distribution, and backordering activities and maximise the customer satisfaction level over the tactical planning horizon. The AUGMECON technique is applied to handle with the multiobjective optimisation. The applicability and the performance of the proposed model are tested through a real-life case study inspired from a medium-sized Tunisian textile and apparel company. Sensitivity analysis on stochastic parameters and managerial insights for the studied supply chain network are argued based on the empirical findings.

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Section: Related Literaturementioning

confidence: 99%

“…e shipping quantity of products between plants is delimited in equation (16) and the distribution capacity to customers in constraint (17). e constraint set (18) enforces the nonnegativity of decision variables.…”

Section: Iptmentioning

confidence: 99%

An Integrated Production-Distribution Planning Problem under Demand and Production Capacity Uncertainties: New Formulation and Case Study

Abid

Ayadi

Masmoudi

2020

Mathematical Problems in Engineering

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“…Economists and policymakers favor the carbon tax as it requires lesser administration in its implementation [13,32]. The cap-and-trade policy offers the opportunity for firms to share the benefits of low-emission activities by carbon trading [33]. The review shows that most of the research focuses on the activities associated with the forward flows in a supply system, only a few studies have explored the decisions for CLSCs.…”

Section: Drivers and Actorsmentioning

confidence: 99%

The Design of Green Supply Chains under Carbon Policies: A Literature Review of Quantitative Models

Elomri

Pokharel

et al. 2019

Sustainability

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Carbon footprinting of products and services is getting increasing attention due to the growing emphasis on carbon related policies in many countries. As a result, many enterprises are focusing on the design of green supply chains (GSCs) with research on supply chains (SCs) focused not only on cost efficiency, but also on its environmental consequences. The review presented in this paper focuses on the implications of carbon policies on SCs. The concept of content analysis is used to retrieve and analyze the information regarding drivers (carbon policies), actors (for example, manufacturers and retailers), methodologies (mathematical modeling techniques), decision-making contexts (such as, facility location and order quantity), and emission reduction opportunities. The review shows a lack of emissions analysis of SCs that face carbon policies in different countries. The research also focuses on the design of carbon policies for emissions reduction in different operating situations. Some possible research directions are also discussed at the end of this review.

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“…They considered the probabilistic lead times in order to improve performance of the system and presented a Pareto-based multi-objective harmony search algorithm. Recently, Entezaminia et al [61] proposed a robust multi-objective multi-site APP model in a green SC by considering the reverse logistics network. They took into account some green principles such as waste management, greenhouse gas emissions related to transportation modes, and production methods.…”

Section: Review Of the Literature On Production Planning And Appmentioning

confidence: 99%

“…It also should be noted that some basic studies have used this approach for the APP and they note that \as economic scenarios are taken into account, changes in uncertain data do not have signi cant e ect on an optimized production planning" [7,64]. The interested readers can refer to references [10,61,[65][66][67][68][69][70][71] to obtain more information about the robust optimization ap-proach. In this paper, the amounts of production and inventory are considered as control variables.…”

Section: Problem Descriptionmentioning

confidence: 99%

Benders Decomposition Algorithm for Robust Aggregate Production Planning Considering Pricing Decisions in Competitive Environment: A Case Study

Aazami

Saidi‐Mehrabad

2018

Scientia Iranica

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In operations research, bi-level programming is a mathematical modeling which has another optimization problem as a constraint. In the present research, regarding the current intense competition among large manufacturing companies for achieving a greater market share, a bi-level robust optimization model is developed as a leader-follower problem using Stackelberg game in the eld of Aggregate Production Planning (APP). The leader company with higher in uence intended to produce new products, which could replace the existing products. The follower companies, as rivals, were also seeking more sales, but they did not have the intention and ability to produce such new products. The price of the new products was determined by the presented elasticity relations between uncertain demand and price. After linearization, using the KKT conditions, the bi-level robust model was transformed into an ordinary uni-level model. Due to the NP-hard nature of the problem, Benders Decomposition Algorithm (BDA) was proposed for overcoming the computational complexities in large scale. Finally, using the real data of Sarvestan Sepahan Co as a leader company, the validity of the developed model as well as e ciency and convergence of the BDA was investigated. The computational results clearly showed the e ciency and e ectiveness of the proposed BDA.

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Robust aggregate production planning in a green supply chain under uncertainty considering reverse logistics: a case study

Cited by 49 publications

References 43 publications

An Integrated Production-Distribution Planning Problem under Demand and Production Capacity Uncertainties: New Formulation and Case Study

An Integrated Production-Distribution Planning Problem under Demand and Production Capacity Uncertainties: New Formulation and Case Study

The Design of Green Supply Chains under Carbon Policies: A Literature Review of Quantitative Models

Benders Decomposition Algorithm for Robust Aggregate Production Planning Considering Pricing Decisions in Competitive Environment: A Case Study

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