Solving a New Multi-Period Multi-Objective Multi-Product Aggregate Production Planning Problem Using Fuzzy Goal Programming

Khalili‐Damghani, Kaveh; Shahrokh, Ayda

doi:10.7232/iems.2014.13.4.369

Cited by 11 publications

(21 citation statements)

References 43 publications

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“…Khalili-Damghani and Shahrokh (2014) proposed a multi-period multi-objective multiproduct aggregate production planning problem. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of end product, were considered, simultaneously.…”

Section: Literature Of Past Workmentioning

confidence: 99%

“…Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of end product, were considered, simultaneously. Several constraints were also considered by Khalili-Damghani and Shahrokh (2014). The proposed problem was solved using Fuzzy Goal Programming (FGP) approach (KhaliliDamghani and Shahrokh, 2014).…”

Section: Literature Of Past Workmentioning

confidence: 99%

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Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

Khalili‐Damghani

Shahrokh

Pakgohar

2017

Int. J. Prod. Manag. Eng.

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In this paper a multi-period multi-product multi-objective aggregate production planning (APP) model is proposed for an uncertain multi-echelon supply chain considering financial risk, customer satisfaction, and human resource training. Three conflictive objective functions and several sets of real constraints are considered concurrently in the proposed APP model. Some parameters of the proposed model are assumed to be uncertain and handled through a two-stage stochastic programming (TSSP) approach. The proposed TSSP is solved using three multi-objective solution procedures, i.e., the goal attainment technique, the modified ε-constraint method, and STEM method. The whole procedure is applied in an automotive resin and oil supply chain as a real case study wherein the efficacy and applicability of the proposed approaches are illustrated in comparison with existing experimental production planning method.

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Section: Literature Of Past Workmentioning

confidence: 99%

Section: Literature Of Past Workmentioning

confidence: 99%

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

Khalili‐Damghani

Shahrokh

Pakgohar

2017

Int. J. Prod. Manag. Eng.

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View full text Add to dashboard Cite

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Section: Literature Of Past Workmentioning

confidence: 99%

“…Several constraints were also considered by Khalili-Damghani and Shahrokh (2014). The proposed problem was solved using Fuzzy Goal Programming (FGP) approach (Khalili-Damghani and Shahrokh, 2014). Min (2015) proposed a supply chain consisting of a manufacturer under emissions regulation and a permit supplier.…”

Section: Literature Of Past Workmentioning

confidence: 99%

“…The main contribution of this research are as follows: 1) proposing a DDM approach for a multi-product sup- Khalili-Damghani andGhasemi: Industrial Engineering &Management Systems Vol 15, No 2, June 2016, pp.156-172, © 2016 KIIE 170 ply chain planning problem while the production and distribution problems in supply chain are addressed independently in manufacturer and retailers; 2) Extension of both CDM and DDM approaches in presence of demand uncertainty using fuzzy sets; 3) Introducing a coordination mechanism in the proposed DDM approach in order to handle problems related to production and distribution in a two-echelon supply chain network through a decentralized approach and in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multi-product supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches.…”

Section: Conclusion Remarks and Future Research Directionsmentioning

confidence: 99%

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Uncertain Centralized/Decentralized Production-Distribution Planning Problem in Multi-Product Supply Chains: Fuzzy Mathematical Optimization Approaches

Khalili‐Damghani¹,

Ghasemi²

2016

Industrial Engineering and Management Systems

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Complex and uncertain issues in supply chain result in integrated decision making processes in supply chains. So decentralized (distributed) decision making (DDM) approach is considered as a crucial stage in supply chain planning. In this paper, an uncertain DDM through coordination mechanism is addressed for a multi-product supply chain planning problem. The main concern of this study is comparison of DDM approach with centralized decision making (CDM) approach while some parameters of decision making are assumed to be uncertain. The uncertain DDM problem is modeled through fuzzy mathematical programming in which products' demands are assumed to be uncertain and modeled using fuzzy sets. Moreover, a CDM approach is customized and developed in presence of fuzzy parameters. Both approaches are solved using three fuzzy mathematical optimization methods. Hence, the contribution of this paper can be summarized as follows: 1) proposing a DDM approach for a multi-product supply chain planning problem; 2) Introducing a coordination mechanism in the proposed DDM approach in order to utilize the benefits of a CDM approach while using DDM approach; 3) Modeling the aforementioned problem through fuzzy mathematical programming; 4) Comparing the performance of proposed DDM and a customized uncertain CDM approach on multiproduct supply chain planning; 5) Applying three fuzzy mathematical optimization methods in order to address and compare the performance of both DDM and CDM approaches. The results of these fuzzy optimization methods are compared. Computational results illustrate that the proposed DDM approach closely approximates the optimal solutions generated by the CDM approach while the manufacturer's and retailers' decisions are optimized through a coordination mechanism making lasting relationship. .

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A systematic review of aggregate production planning literature with an outlook for sustainability and circularity

Aydın

Tirkolaee

2022

Environ Dev Sustain

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Solving a New Multi-Period Multi-Objective Multi-Product Aggregate Production Planning Problem Using Fuzzy Goal Programming

Cited by 11 publications

References 43 publications

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

Stochastic multi-period multi-product multi-objective Aggregate Production Planning model in multi-echelon supply chain

Uncertain Centralized/Decentralized Production-Distribution Planning Problem in Multi-Product Supply Chains: Fuzzy Mathematical Optimization Approaches

A systematic review of aggregate production planning literature with an outlook for sustainability and circularity

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