A multi-objective programming method for solving network DEA

Kao, Han-Ying; Chan, Chieh-Yu; Wu, Dong-Jyun

doi:10.1016/j.asoc.2014.06.057

Cited by 36 publications

(35 citation statements)

References 26 publications

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“…In the proposed method, the divisional e ciencies (within an organization) and the overall e ciency of the organization were formulated as separate objective functions in the multiobjective programming model [24]. Despotis et al also used multi-objective programming approach for solving a network DEA problem [25].…”

Section: Literature Reviewmentioning

confidence: 99%

Efficiency assessment of Iranian Handmade Carpet Company by network DEA

Zegordi

Omid

2017

Scientia Iranica

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Abstract. Di erent categories of Iranian handmade carpet are produced each year. Due to resource limitation, it is so important for managers to allocate more resources to the most e cient categories. Therefore, the main purpose of this illustration is to consider most e cient types of carpet in production and sales stages. To do so, di erent categories of Iranian handmade carpet are considered as DMUs. This study utilizes network DEA for constructing a model to analyze total and partial e ciencies of Iranian Handmade Carpet Company (IHCC), simultaneously. IHCC consists of three main departments that are working jointly to maximize productivity of the rm; therefore, the case of IHCC is a multi-stage system with shared intermediate variables, extra inputs to the second stage, and undesired outputs. The novelty of this paper is the methodology used for calculating the e ciency, which is based on multi-objective programming. Results of experimental data of IHCC are summarized in order to prepare some brilliant management strategies based on partial and total e ciency scores of di erent carpet categories. Because of the lack of familiar researches in the area of carpet industry e ciency measurement, this research will provide valuable information for decision makers.

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Section: Literature Reviewmentioning

confidence: 99%

Efficiency assessment of Iranian Handmade Carpet Company by network DEA

Zegordi

Omid

2017

Scientia Iranica

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“…There are different methods to solve the two objective model 9. In this study Fuzzy method [10] is applied. General algorithm of this method is presented in section 5.…”

Section: Two-stage Dea Modelmentioning

confidence: 99%

“…Where: To solve the above model (Model 10) through fuzzy method [10], the following operation was performed:…”

Section: K-stage Model Ndea-ccr In the Presence Of Semi-positive And mentioning

confidence: 99%

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The NDEA–MOP Model in the Presence of Negative Data Using Fuzzy Method

et al. 2017

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In this study, the multi-objective programming (MOP) method was used to solve network DEA (NDEA) models with assumption that, negative data is considered for the proposed NDEA model which consists of semi-negative and semi-positive input and output. At first, two stage and then k stage production models were formulated with consideration of negative data. In the multi-objective programming, two separate objective functions including the divisional efficiencies and the overall efficiency of the organization are modeled. In comparison to conventional DEA with negative data, the advantage of the proposed NDEA 2 models is consideration of intermediate processes and products, in order to calculate the organization's overall efficiency. However, in conventional DEA, sub-stages of the organizations are neglected. To measure the efficiencies of an organization regarding interactive internal process, two case studies were investigated by application of the NDEA-MOP method with negative data. Case study 1 is focused on units with two stages having semi-negative and semi-positive indexes. In case study 2, units with three stages are evaluated. These units also have semi-negative and semi-positive indexes. The overall efficiency of each unit is calculated using the proposed models. Fuzzy approach as a solution procedure is applied.

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“…In the literature of supply chain network design problems, to make the models more realistic, several objectives are considered together (Murillo-Alvarado et al 2015;Pasandideha et al 2015;Godichaud and Amodeo 2015;Gholamian et al 2015). Besides, the solution of multi-objective problems is both attractive and challenging (Kao et al 2014;Jadidia et al 2015;Ghodratnama et al 2015;Validi et al 2014).…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

A meta-heuristic approach supported by NSGA-II for the design and plan of supply chain networks considering new product development

et al. 2017

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There are many reasons for the growing interest in developing new product projects for any firm. The most embossed reason is surviving in a highly competitive industry which the customer tastes are changing rapidly. A well-managed supply chain network can provide the most profit for firms due to considering new product development. Along with profit, customer satisfaction and production of new products are goals which lead to a more efficient supply chain. As new products appear in the market, the old products could become obsolete, and then phased out. The most important parameter in a supply chain which considers new and developed products is the time that developed and new products are introduced and old products are phased out. With consideration of the factors noted above, this study proposes to design a tri-objective multi-echelon multiproduct multi-period supply chain model, which incorporates product development and new product production and their effects on supply chain configuration. The supply chain under consideration is assumed to consist of suppliers, manufacturers, distributors and customer groups. In terms of overcoming NP-hardness of the proposed model and in order to solve the complicated problem, a non-dominated sorting genetic algorithm is employed. As there is no benchmark available in the literature, the non-dominated ranking genetic algorithm is developed to validate the results obtained and some test problems are provided to show the applicability of the proposed methodology and evaluate the performance of the algorithms.

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A multi-objective programming method for solving network DEA

Cited by 36 publications

References 26 publications

Efficiency assessment of Iranian Handmade Carpet Company by network DEA

Efficiency assessment of Iranian Handmade Carpet Company by network DEA

The NDEA–MOP Model in the Presence of Negative Data Using Fuzzy Method

A meta-heuristic approach supported by NSGA-II for the design and plan of supply chain networks considering new product development

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