A multi-objective model for multi-product multi-site aggregate production planning in a green supply chain: Considering collection and recycling centers

Entezaminia, Arezoo; Heydari, Mojtaba; Rahmani, Donya

doi:10.1016/j.jmsy.2016.06.004

Cited by 85 publications

(27 citation statements)

References 40 publications

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“…Deterministic Single Aghezzaf & Artiba, 1998;Silva & JoÄOoisboa, 2000;Pradenas & Pe˜nailillo, 2004;Fahimnia et al, 2005;Pipery & Vachony, 2001;Singhvi & Shenoy, 2002;Techawiboonwong & Yenradee, 2003;Mazzola et al, 1998;Sillekens et al, 2011;Zhang et al, 2012;Ramezanian et al, 2012;Chaturvedi & Bandyopadhyay, 2015;Chaturvedi, 2017Multiple Leung & Chan, 2009Leung et al, 2003;Chakrabortty & Akhtar Hasin, 2013;Entezaminia et al, 2016;Abu Bakar et al, 2016;Mehdizadeh et al, 2018 Uncertain Fuzzy Single Baykasoglu, 1999;Wang & Fang, 2000;Fung et al, 2003;Tang et al, 2000;Tang et al, 2003;Ning et al, 2006;Aliev et al, 2007;Chen & Huang, 2010;Iris & Cevikcan, 2014;Rahmani et al, 2014;Chakrabortty et al, 2015Multiple Wang & Fang, 1997Baykasoglu & Gocken, 2006;Sakallı et al, 2010;Baykasoglu & Gocken, 2010;Sadeghi et al, 2013;da Silva & Silva Marins, 2014;Gholamian et al, 2016;Fiasché et al, 2016;Chauhan et al, 2017;…”

Section: Objective Function Articlesmentioning

confidence: 99%

Aggregate production planning: A literature review and future research directions

Cheraghalikhani¹,

Khoshalhan²,

Mokhtari³

2019

10.5267/j.ijiec

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Aggregate production planning (APP) is concerned with determining the optimum production and workforce levels for each period over the medium term planning horizon. It aims to set overall production levels for each product family to meet fluctuating demand in the near future. APP is one of the most critical areas of production planning systems. After the state-of-the-art summaries in 1992 by Nam and Logendran [ Nam, S. J., & Logendran, R. (1992). Aggregate production planning-a survey of models and methodologies. European Journal of Operational Research, 61(3), 255-272. ], which specifically summarized the various existing techniques from 1950 to 1990 into a framework depending on their abilities to either produce an exact optimal or near-optimal solution, there has not been any systematic survey in the literature. This paper reviews the literature on APP models to meet two main purposes. First, a systematic structure for classifying APP models is proposed. Second, the existing gaps in the literature are demonstrated in order to extract future directions of this research area. This paper covers a variety of APP models' characteristics including modeling structures, important issues, and solving approaches, in contrast to other literature reviews in this field which focused on methodologies in APP models. Finally some directions for future research in this research area are suggested.

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Section: Objective Function Articlesmentioning

confidence: 99%

Aggregate production planning: A literature review and future research directions

Cheraghalikhani¹,

Khoshalhan²,

Mokhtari³

2019

10.5267/j.ijiec

View full text Add to dashboard Cite

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“…Aggregate production planning (APP) addresses the question, "How should a company best use the equipment and facilities that it currently has?" (Chopra and Meindl 2007). Accurate demand forecast and supply constraints are two key important inputs of APP.…”

Section: Introductionmentioning

confidence: 99%

Cooperative aggregate production planning: a game theory approach

2019

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Production costs in general, and workforce and inventory costs in particular, constitute a large fraction of the operating costs of many manufacturing plants. We introduce cooperative aggregate production planning as a way to decrease these costs. That is, when production planning of two or more facilities (plants) is integrated, they can interchange workforce and products inventory; thus, their product demands can be satisfied at lower cost. This paper quantifies the cost saving and synergy of different coalitions of production plants by a new linear model for cooperative aggregate planning problem. The developed approach is explicated with a numerical example in which inventory and workforce levels of different coalitions of facilities are evaluated. Afterward, a key question would be how the cost saving of a coalition should be divided among members. We tackle the problem using different methods of cooperative game theory. These methods are implemented in the numerical example to gain an insight into properties of the corresponding game results.

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“…They considered demand, capacity, and greenness expectations of manufacturers, carriers, distribution centers, and retailers to construct an MIP model and applied goal programming to solve the proposed model. Entezaminia et al [27] integrated collection and recycling centers into a green supply chain network; its features consisted of multi-period, multi-product, multi-transportation mode, and multisite factors. For the green concept, they added the limitations of CO 2 emissions in both production and transportation as constraints and added one objective function.…”

Section: Introductionmentioning

confidence: 99%

“…Multi-objective function (total income, total cost, total market penalty, total market bonus, and total lost sales), lost sales, and greenness expectation GSC Entezaminia et al [27] } } } } } } }…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimization of Green Supply Chain Network Designs for Transportation Mode Selection

Gong

Chen

2017

Scientia Iranica

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Abstract. This research considers both cost and environmental protection to design a multi-objective optimization model. With multi-period customer demands, the model can solve a multi-plant resource allocation and production planning problem by focusing the decisions on supplier selection, facility selection, production batches, transportation mode selection, and distribution of the materials and commodities of a green supply network. In this paper, four transportation modes, namely, road, rail, air, and sea, have their corresponding transportation time, costs, and CO 2 emissions. Based on multiple planning periods, this research calculates the minimal total cost and total CO2 emissions based on production and transportation capacity. Using numerical analyses, the results show that, when the budget is su cient, only production capabilities with = 1:5 and 2.0 are bene cial for improving environmental protection; carbon dioxide emissions of both production capacities are not signi cantly di erent. Furthermore, when the production batch size increases, total cost increases. Regarding transportation capacity, the results show that, when the budget is su cient, increasing transportation quantity limits will be slightly bene cial for improving environmental protection.

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A multi-objective model for multi-product multi-site aggregate production planning in a green supply chain: Considering collection and recycling centers

Cited by 85 publications

References 40 publications

Aggregate production planning: A literature review and future research directions

Aggregate production planning: A literature review and future research directions

Cooperative aggregate production planning: a game theory approach

Multi-Objective Optimization of Green Supply Chain Network Designs for Transportation Mode Selection

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