A new normalized goal programming model for multi-objective problems: A case of supplier selection and order allocation

Jadidi, Omid; Zolfaghari, Saeed; Cavalieri, Sergio

doi:10.1016/j.ijpe.2013.10.005

Cited by 110 publications

(49 citation statements)

References 29 publications

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“…Using the functions defined above, MOO problem considering the supplier selection with order allocation can be formulated as follows [12]:…”

Section: Proposed Modelmentioning

confidence: 99%

“…Therefore, the overall supplier selection problem should not only cover the selection of the right supplier but also the determination of the orders assigned to the selected supplier based on the given objectives and constraints [8]. To date, however, only a few mathematical programming models to analyze such decisions have been published [9][10][11][12]. In the field of supply chain management, it is necessary to develop a precise decision support model which simultaneously considers supplier selection and order allocation.…”

Section: Introductionmentioning

confidence: 99%

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An Interactive Multiobjective Optimization Approach to Supplier Selection and Order Allocation Problems Using the Concept of Desirability

Lee

Kang

2018

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Abstract:In supply chain management, selecting the right supplier is one of the most important decision-making processes for improving corporate competitiveness. In particular, when a buyer considers selecting multiple suppliers, one should consider the issue of order allocation with supplier selection. In this article, an interactive multiobjective optimization approach is proposed for the supplier selection and order allocation problem. Also, the concept of desirability is incorporated into the optimization model to take into account the principles of diminishing marginal utility. The results are presented by comparing them with the solutions from the weighting methods. This study shows the advantage of the proposed method in that the decision-maker directly checks the degree of desirability and learns his/her preference structure through improved solutions.

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“…Using the functions defined above, MOO problem considering the supplier selection with order allocation can be formulated as follows [12]:…”

Section: Proposed Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Interactive Multiobjective Optimization Approach to Supplier Selection and Order Allocation Problems Using the Concept of Desirability

Lee

Kang

2018

Information

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“…Hence, various models have been developed in this area. Most popular single approaches are Analytic hierarchy process (AHP) [4], TOPSIS [5], VIKOR [6], Analytic network process (ANP) [7], Goal programming (GP) [8], multi objective programming [9], Data envelopment analysis S. N. Musa et al J Fundam Appl Sci. 2017, 9(4S), 417-429 419 (DEA) [10], Fuzzy set theory (FST) [11][12], etc.…”

Section: Fig1 Supply Chain Systemmentioning

confidence: 99%

A hybrid fuzzy multi-criteria decision making model for green supplier selection

Hashemzahi¹,

Musa²,

Yusof³

2018

J. Fundam and Appl Sci.

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“…Their model is based on Multi-objective optimization as well as non-dominated sorting genetic algorithm II (NSGA II). Jadidi et al (2014) designed a multi-objective optimization problem (MOOP) where minimization of price, rejects and lead-time were considered as three objectives using TOPSIS, weighted goal programming, Min-max goal programming and weighted max-min model for supplier selection problem. Guo et al (2014) presented a semi-fuzzy support vector domain description (semi-fuzzy SVDD) for supplier selection problem.…”

Section: Literaturesmentioning

confidence: 99%

A supplier selection using a hybrid grey based hierarchical clustering and artificial bee colony

Razi¹

2014

10.5267/j.dsl

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Selection of one or a combination of the most suitable potential providers and outsourcing problem is the most important strategies in logistics and supply chain management. In this paper, selection of an optimal combination of suppliers in inventory and supply chain management are studied and analyzed via multiple attribute decision making approach, data mining and evolutionary optimization algorithms. For supplier selection in supply chain, hierarchical clustering according to the studied indexes first clusters suppliers. Then, according to its cluster, each supplier is evaluated through Grey Relational Analysis. Then the combination of suppliers' Pareto optimal rank and costs are obtained using Artificial Bee Colony meta-heuristic algorithm. A case study is conducted for a better description of a new algorithm to select a multiple source of suppliers.

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A new normalized goal programming model for multi-objective problems: A case of supplier selection and order allocation

Cited by 110 publications

References 29 publications

An Interactive Multiobjective Optimization Approach to Supplier Selection and Order Allocation Problems Using the Concept of Desirability

An Interactive Multiobjective Optimization Approach to Supplier Selection and Order Allocation Problems Using the Concept of Desirability

A hybrid fuzzy multi-criteria decision making model for green supplier selection

A supplier selection using a hybrid grey based hierarchical clustering and artificial bee colony

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