2019
DOI: 10.30880/ijie.2019.11.06.009
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A Bi-Objective Programming Model for Reliable Supply Chain Network Design under Facility Disruption

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Cited by 12 publications
(9 citation statements)
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“…Equation 1has the same objective function and uses the same optimization approach as the Simple Additive Weighted (SAW) method. [23]. Each entity will accumulate one score.…”
Section: Model Specification 211 Operation Research Modelingmentioning
confidence: 99%
“…Equation 1has the same objective function and uses the same optimization approach as the Simple Additive Weighted (SAW) method. [23]. Each entity will accumulate one score.…”
Section: Model Specification 211 Operation Research Modelingmentioning
confidence: 99%
“…Disruptions in production planning are generally associated with the interruptions such as machine breakdown, lack of professional workers, failure to get reused item, mismatch of process timing occurring during the production process that may have an impact on its rate of production and product quality [20], [21]. For this reason, while disruptions on a carefully planned production flow can be regarded as impairing a company's performance, the outcome of a company's rate of production, on the other hand, can thus be seen as being influenced by those affecting its infrastructure facilities.…”
Section: Resultsmentioning
confidence: 99%
“…As such, the complexities of the production planning in the remanufacturing process would very much depend on the reuse methods being employed, types of remanufactured products as well as the quality and quantity of the returned products. Since it is essential for the returned parts to undergo inspection before they can be transformed into raw materials or disassembled for reuse [19][20], the manufacturer would then be required to assimilate the production of a remanufacturing product with newly purchased parts from the suppliers and the recovered parts from the returned products [25].…”
Section: Production Planningmentioning
confidence: 99%
“…Information is full of uncertainty in the real world [1][2][3][4], so it is important to develop the technology to deal with the uncertain information.Amounts of models and theories are proposed for uncertainty modeling, such as Dempster-Shafer evidence theory [5,6], Z numbers [7,8], fuzzy sets theory [9][10][11], and other models [12][13][14][15]. Those models are widely used in real-world applications, including multi-criteria decision making [16][17][18], reliability analysis [19][20][21][22], classification [23,24], complex network [25][26][27], medical diagnosis [28,29], and risk analysis [30,31].…”
Section: Introductionmentioning
confidence: 99%