A decision-making methodology for vendor selection problem with uncertain inputs

Azadeh, A.; Rahimi, Yaser; Zarrin, Mansour; Ghaderi, Abolfazl; Shabanpour, N.

doi:10.1080/19427867.2016.1188525

Cited by 13 publications

(6 citation statements)

References 42 publications

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“…Many fuzzy/possibilistic methods have been introduced in the literature. In a typical fuzzy approach, a novel fuzzy programming model is converted to a conventional mathematical model, then an optimization technique is used to solve the converted mathematical model (Azadeh et al 2017;Rahimi et al 2018;Mollanoori et al 2019;Haghjoo et al 2020;Kaveh et al 2021). At the end, if the determined optimal solution is not acceptable, the fuzzy model is rebuilt based on the improved interpretation (Inuiguchi and Ramık, 2000).…”

Section: Solution Approachmentioning

confidence: 99%

Modelling and solving the bi-objective production–transportation problem with time windows and social sustainability

Shahrabi

Tavakkoli–Moghaddam

Triki

et al. 2021

IMA Journal of Management Mathematics

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We model and solve the production routing problem (PRP) with time windows, product deterioration and split delivery. A bi-objective PRP model for a single perishable product, which is subject to deterioration, is presented. The two objectives represent the economic and social aspects of sustainability, whereas the environmental impact is enforced by incorporating ad-hoc constraints. The economic dimension of sustainability consists of minimizing the costs related to the production, setup, holding, transportation and lateness penalty. The social responsibilities are modelled through maximizing the total freshness of the delivered products at all nodes over the planning horizon. The outcomes of our formulation are represented by the lot sizes, and the amounts of product to be delivered, as well as the routing at each planning period. To solve the resulting problem, we develop an interval robust possibilistic approach, and we carry out an experimental study and a sensitivity analysis. Finally, we further validate our optimization model and solution method using a real-life case of a food factory producing a product that is subject to perishability and deterioration.

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Section: Solution Approachmentioning

confidence: 99%

Modelling and solving the bi-objective production–transportation problem with time windows and social sustainability

Shahrabi

Tavakkoli–Moghaddam

Triki

et al. 2021

IMA Journal of Management Mathematics

Self Cite

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“…Ghorabaee et al (2017) provided a review of applications of multi-attribute decision-making approaches in the field of VSP. Azadeh et al (2017) used certainty, uncertainty and stochastic conditions and used appropriate tools while assessing six criteria to solve the VSP model under these conditions. They have not considered vendor ratings and vendor quota flexibilities.…”

Section: Literature Reviewmentioning

confidence: 99%

A bi-level decision-making approach for the vendor selection problem with random supply and demand

Muneeb

Nomani

Masmoudi

et al. 2019

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Purpose Supplier selection problem is the key process in decision making of supply chain management. An effective selection of vendors is heavily responsible for the success of any organization. Vendor selection problem (VSP) reflects a more practical view when the decision makers involved in the problem are present on different levels. Moreover, vendor selection consists of various random parameters to be dealt with in real life. The purpose of this paper is to present a decentralized bi-level VSP where demand and supply are normal random variables and objectives are fuzzy in nature. Decision makers are present at two levels and are called as leader and follower. As the next purpose, this paper extends and presents a solution approach for fuzzy bi-level multi-objective decision-making model with stochastic constraints. Different scenarios have been developed within a real-life case study based on different sets of controlling factors under the control of leader. Design/methodology/approach This study uses chance-constrained programming and fuzzy set theory to generate the results. Stochastic constraints are converted into deterministic constraints using chance-constrained programming. Decision variables in the bi-level VSP are partitioned between the two levels and considered as controlling factors. Membership functions based on fuzzy set theory are created for the goals and controlling factors and are used to obtain the overall satisfactory solutions. The model is tested on a real-life case study of a textile industry and different scenarios are constructed based on the choice of leader’s controlling factors. Findings Results showed that the approach is quite helpful as it generates efficient results producing a good level of satisfaction for the decision makers of both the levels. Results showed that on choosing the vendors that are associated with worst values in terms of associated costs, vendor ratings and quota flexibilities as controlling factors by the leaders, the level of satisfaction achieved is highest. The level of satisfaction of solution is lowest for the scenario when the leader chooses to control the decision variables associated with vendors that are profiled with minimum vendor ratings. Results also showed that higher availability of materials and budget with vendors proved helpful in obtaining quota allocations. Different scenarios generate different results along with different values of satisfaction degrees and objective values which shows the flexible feature of the approach based on leader’s choice of controlling factors. Numerical results showed that the leader’s control can be effectively incorporated maintaining satisfaction levels of the followers under various scenarios or conditions. Research limitations/implications The paper makes a certain contribution toward the study of vendor selection existing in a hierarchical manner under uncertain environment. A wide set of data of different factors is needed which can be seen as a limitation when the available time is short for the supplier selection process. Practical implications VSP which is generally adopted by most of the large organizations is characterized with hierarchical decision making. Moreover, dealing with the real-life concern, the data available for some of the parameters are not complete, representing an uncertainty of parameters. This study is quite helpful for decentralized VSP under uncertain environment to reduce the costs, improve profit margins and to create long-term relationships with selected vendors. The proposed model also provides an avenue to explore the decision making when the leader has control over some of the decision variables. Originality/value Reviewing the literature available, this is the first attempt to present a multi-objective VSP where the decision makers are at hierarchical levels considering uncertain parameters such as demand and supply as per the best knowledge of authors. This research further provides an approach to construct scenarios or different cases based on the choice of leader’s choice of controlling factors.

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“…The second direction is to extend DEA to be able to handle random errors in data based on the bootstrap technique (Simar and Wilson 1998 ; Lothgren and Tambour 1999 ). The last direction is to extend DEA to regard the estimated frontier as a random or stochastic frontier, also based on random variation in the data (Huang and Li 2001 ; Ruggiero 2004 ; Kao and Liu 2009 ; Azadeh et al 2017 ). These three directions have their own limitations.…”

Section: Introductionmentioning

confidence: 99%

Estimating the confidence intervals for DEA efficiency scores of Asia-Pacific airlines

Ngo

Tsui

2021

Oper Res Int J

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Data envelopment analysis (DEA) is a popular non-parametric approach to examine performance and productivity of airlines; however, it could not provide statistical information such as confidence intervals on the estimated efficiency scores. We combined stochastic frontier analysis and DEA into a single framework to disentangle noise and ‘pure’ inefficiency from the DEA inefficiency scores and accordingly provide confidence intervals for the estimated efficiency scores. Monte-Carlo simulation verified that our novel model is a good alternative for the conventional DEA as well as the bootstrap DEA. Empirical application using Asia-Pacific airlines’ data (2008‒2015) shows that after accounting for the ‘pure’ random errors, the sampled Asia-Pacific airlines performed well during the study period but their ‘pure’ efficiency was declining, hence, there is still room for improvement.

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A decision-making methodology for vendor selection problem with uncertain inputs

Cited by 13 publications

References 42 publications

Modelling and solving the bi-objective production–transportation problem with time windows and social sustainability

Modelling and solving the bi-objective production–transportation problem with time windows and social sustainability

A bi-level decision-making approach for the vendor selection problem with random supply and demand

Estimating the confidence intervals for DEA efficiency scores of Asia-Pacific airlines

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