Fuzzy optimization for supply chain planning under supply, demand and process uncertainties

Peidro, David; Mula, Josefa; Mula, Josefa; Verdegay, J. L.

doi:10.1016/j.fss.2009.02.021

Cited by 228 publications

(119 citation statements)

References 76 publications

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“…The following is the step of carrying out this method [18]:  The 1st step: defining the problem and determining its aim.  The 2nd step: creating the hierarchical structure from top to the medial levels and to the lowest level of the problem being the collection of the alternatives.…”

Section: Fuzzy Hierarchical Analysis Methodmentioning

confidence: 99%

Choosing An Appropriate Factorial System Through The Modern And Outmoded System By Two Approaches Anp Ahp-fuzzy

Abdollahzadeh¹,

Amiri²,

Kaffash³

et al. 2013

J. Math. Computer Sci.

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Today, by introducing the factorial modern systems to the construction industry of the country, it is not easy to make a decision in order to use these modern systems together with the outmoded and conventional systems .Regarding the unique traits in each of these systems, and the special conditions of each project, it is possible that each of these systems to have a priority over the factorial systems prevailing in the country. Thus, it was made an effort to choose the most appropriate factorial system through the modern and outmoded systems in the country using the multi criteria making decision methods, ANP and AHP-FUZZY, and regarding some of the important criteria in choosing the type of the factorial system such as dead load, saving energy, performance facility, etc .finally, light steel frame (LSF) system has been chosen as the most appropriate selection through the ones under study.

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Section: Fuzzy Hierarchical Analysis Methodmentioning

confidence: 99%

Choosing An Appropriate Factorial System Through The Modern And Outmoded System By Two Approaches Anp Ahp-fuzzy

Abdollahzadeh¹,

Amiri²,

Kaffash³

et al. 2013

J. Math. Computer Sci.

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“…Utmost are due to hybrid approaches (due to the accretion of simulation and analytic formulations), simulation approaches, or analytic approaches (i.e., stochastic formulations) (Peidro et al 2009). In these approaches, the SC uncertainties are presented with probability distributions which are commonly forecasted from historical data.…”

Section: Scnd With Parameter Uncertaintymentioning

confidence: 99%

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

Shishebori

Babadi

2017

J Ind Eng Int

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This study investigates the reliable multi-configuration capacitated logistics network design problem (RMCLNDP) under system disturbances, which relates to locating facilities, establishing transportation links, and also allocating their limited capacities to the customers conducive to provide their demand on the minimum expected total cost (including locating costs, link constructing costs, and also expected costs in normal and disturbance conditions). In addition, two types of risks are considered; (I) uncertain environment, (II) system disturbances. A two-level mathematical model is proposed for formulating of the mentioned problem. Also, because of the uncertain parameters of the model, an efficacious possibilistic robust optimization approach is utilized. To evaluate the model, a drug supply chain design (SCN) is studied. Finally, an extensive sensitivity analysis was done on the critical parameters. The obtained results show that the efficiency of the proposed approach is suitable and is worthwhile for analyzing the real practical problems.

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“…Finally an L-shaped decomposition in the master problem was proposed for solving the model. Peidro et al (2009) introduced a unique centralized/decentralized planning model considering production and distribution planning activities for a multi-echelon, multi-product and multi-period SC network. The model was formulated as a fuzzy mixed-integer linear programming (FMILP) in which, objective function was to minimize the total cost including production cost, the costs corresponding to idleness, inventory holding cost, and transport cost.…”

Section: Literature Of Past Workmentioning

confidence: 99%

“…The model was formulated as a fuzzy mixed-integer linear programming (FMILP) in which, objective function was to minimize the total cost including production cost, the costs corresponding to idleness, inventory holding cost, and transport cost. Peidro et al (2009) defined an approach to transform the proposed FMILP into an equivalent auxiliary crisp MILP model.…”

Section: Literature Of Past Workmentioning

confidence: 99%

“…The relevant research works in this area have been reviewed through the last decade and summarized in Table1. As can be seen in Table 1, the previous researches considered demand-side uncertainty (Hegeman et al, 2014;Arikan, 2013;Vahdani et al, 2012;Lu et al, 2012;Pishvae et al, 2011;Peidro et al, 2009;Xu et al, 2008;Selma et al, 2007;Shu et al, 2005). Moreover, it can be deduced that a large number of centralized mathematical programming models have been developed to simultaneously optimize the integration of the entire SC.…”

Section: Literature Of Past Workmentioning

confidence: 99%

See 1 more Smart Citation

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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Fuzzy optimization for supply chain planning under supply, demand and process uncertainties

Cited by 228 publications

References 76 publications

Choosing An Appropriate Factorial System Through The Modern And Outmoded System By Two Approaches Anp Ahp-fuzzy

Choosing An Appropriate Factorial System Through The Modern And Outmoded System By Two Approaches Anp Ahp-fuzzy

Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

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

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