A bi-objective integrated procurement, production, and distribution problem of a multi-echelon supply chain network design: A new tuned MOEA

Sarrafha, Keyvan; Rahmati, Seyed Habib A.; Niaki, Seyed Taghi Akhavan; Zaretalab, Arash

doi:10.1016/j.cor.2014.08.010

Cited by 121 publications

(39 citation statements)

References 35 publications

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“…The two objectives of this model are minimizing warehouse space and costs. Sarrafha et al [20] proposed a bi-objective mixed-integer nonlinear programming for integrated production, procurement and distribution problem which minimizes costs and the average tardiness of products to distribution centers.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Constraint (19) shows that delivery quantity from distribution centers to customers is equal to or less than customers' demands. Constraint (20) represents the balancing equation for distribution centers. Constraints (21) and (22) show that only one type of vehicle can be selected for each item at every period in each channel.…”

Section: Mathematical Formulations Of Modelmentioning

confidence: 99%

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A fuzzy dynamic multi-objective, multi-item model by considering customer satisfaction in supply chain

et al. 2017

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Abstract. Customer satisfaction is an important issue in competitive strategic management of companies. Logistical and cross-functional drivers of supply chain have an important role in managing customer satisfaction. Customer satisfaction depends on quality, cost, and delivery. In this paper, a fuzzy mixed integer nonlinear programming model is proposed for a multi-item multi-period problem in a multi-level supply chain. Minimization of costs, manufacturing and transportation time, transportation risks, maximization of quality by minimizing the number of defective products, and maximization of customers' service levels are considered to be objective functions of the model. Furthermore, it is assumed that the demand rates are fuzzy values. An exact "-constraint approach is used to solve the problem. The problem is computationally intractable. Therefore, the Non-dominant Sorting Genetic Algorithm (NSGA-II) is developed to solve it. The Taguchi method is utilized to tune the NSGA-II parameters. Finally, some numerical examples are generated and solved to evaluate the performance of the proposed model and solving methods.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Mathematical Formulations Of Modelmentioning

confidence: 99%

A fuzzy dynamic multi-objective, multi-item model by considering customer satisfaction in supply chain

et al. 2017

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“…Multi-level linear programming (MLLP) is a solution technique for solving decentralized decision-making problems. MLLP problems generally include sequential decision processes (from top to bottom), interactive decision makings, and a leader-follower relationship within two adjacent levels (Cao and Chen 2006;Simchi-Levi et al 2004;Lu et al 2007;Karakitsiou and Migdalas 2008;Sarrafha et al 2015). Marinakis and Marinaki (2008) developed a bilevel model in a decentralized decision making environment for capacitated plant selection.…”

Section: Decentralized Supply Chainmentioning

confidence: 99%

“…Liu and Papageorgiou (2013) and Liu et al (2014) proposed multi-objective optimization model for integrated PDP problem in the supply chain. Sarrafha et al (2015) developed a bi-objective model with a multi-periodic structure for an SCN involving suppliers, factories, distribution centers, and retailers. The two objectives were minimizing the total SC cost as well as minimizing the average tardiness of products to DCs and the model was solved using a multi-objective biogeography algorithm.…”

Section: Production-distribution Planning Problemmentioning

confidence: 99%

Optimizing decentralized production–distribution planning problem in a multi-period supply chain network under uncertainty

et al. 2017

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Decentralized supply chain management is found to be significantly relevant in today's competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem's convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy approach and chance constraint approach. Ultimately, a numerical example is constructed and worked through to demonstrate applicability of the optimization model. A sensitivity analysis is also made.

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“…Maximizing the total net income thorough the time is the obvious objective function of the proposed problem. Moreover, Sarrafha et al (2015) studied an SCND containing factories, suppliers, retailers, and DCs. They proposed a multi-period structure such that a flow-shop scheduling formulation in the manufacturing portion of the SC and J Ind Eng Int (2018) 14:65-85 71 also the shortage in the framework of backorder are combined in each period.…”

Section: Scnd With Multi-configurationmentioning

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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A bi-objective integrated procurement, production, and distribution problem of a multi-echelon supply chain network design: A new tuned MOEA

Cited by 121 publications

References 35 publications

A fuzzy dynamic multi-objective, multi-item model by considering customer satisfaction in supply chain

A fuzzy dynamic multi-objective, multi-item model by considering customer satisfaction in supply chain

Optimizing decentralized production–distribution planning problem in a multi-period supply chain network under uncertainty

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

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