2019
DOI: 10.5829/ije.2019.32.11b.15
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A Comprehensive Mathematical Model for a Location-routing-inventory Problem under Uncertain Demand: a Numerical Illustration in Cash-in-transit Sector

Abstract: The purpose of this article is to model and solve an integrated location, routing and inventory problem (LRIP) in cash-in-transit (CIT) sector. In real operation of cash transportation, to decrease total cost and to reduce risk of robbery of such high-value commodity. There must be substantial variation, making problem difficult to formulate. In this paper, to better fit real life applications and to make the problem more practical, a bi-objective multiple periods, capacitated facilities with time windows unde… Show more

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Cited by 1 publication
(2 citation statements)
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References 23 publications
(49 reference statements)
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“…Ali et al [49], while modeling a reverse supply chain, examined its application to air conditioning products. The uncertainty in the considered sustainable supply chain was fuzzy; in fact supply chaimn modeling (SCM) is extensively discussed in literature [50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65]. Locating collection and recycling centers was one of the most important objectives of this study.…”
Section: Modeling Uncertainty In Supply Chainmentioning
confidence: 99%
See 1 more Smart Citation
“…Ali et al [49], while modeling a reverse supply chain, examined its application to air conditioning products. The uncertainty in the considered sustainable supply chain was fuzzy; in fact supply chaimn modeling (SCM) is extensively discussed in literature [50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65]. Locating collection and recycling centers was one of the most important objectives of this study.…”
Section: Modeling Uncertainty In Supply Chainmentioning
confidence: 99%
“…In this section, Mamdani and Asilian's [60] inference system is used due Figure 1. Conceptual model to its simple structure, acceptable results, simplicity of interpreting the results, and its success in previous studies [52][53][54][55].…”
Section: Fuzzy Inference Systemmentioning
confidence: 99%