Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain

Dey, Balaram; Bairagi, Bipradas; Sarkar, Bijan; Sanyal, S.K.

doi:10.1016/j.cie.2016.12.025

Cited by 63 publications

(31 citation statements)

References 35 publications

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“…Therefore, the proposed approach can be effectively applied to energy export security problem. Other real cases of the decision problems that the proposed approach can be applied are the selection of strategic freight forwarder (Zhang et al, ), warehouse location selection (Dey, Bairagi, Sarkar, & Sanyal, ), cloud computing service evaluation (Xu et al, ), and so forth.…”

Section: Resultsmentioning

confidence: 99%

A cumulative belief degree approach for group decision‐making problems with heterogeneous information

Ervural

Kabak

2019

Expert Systems

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In some complex group decision‐making (GDM) problems, the information needing to be processed may be heterogeneous. This may involve consideration of objective and subjective criteria by experts who have their own particular set of criteria, their own preference format for assessing alternatives under these criteria, and who may themselves be assigned differing importance weights as experts. This paper presents a cumulative belief degree approach to cope with heterogeneous information in multiple attribute GDM problems. The proposed approach focuses to aggregate subjective expert assessments and objective criteria that are presented in various representation formats and scales. The methodology employs transformation formulae for several preference representation scales to belief structure, including 2‐tuple representation, classical fuzzy sets, hesitant fuzzy sets, and intuitionistic fuzzy sets. Aggregation formulae are proposed to combine expert criteria evaluations and find a collective preference. A consensus degree is calculated for measuring the agreement between the experts. An illustrative example is presented to clarify the steps of the methodology, and validity of the approach is assured through comparative analysis with the existing methods.

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Section: Resultsmentioning

confidence: 99%

A cumulative belief degree approach for group decision‐making problems with heterogeneous information

Ervural

Kabak

2019

Expert Systems

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“…The methods used in the selection of warehouse location such as multi criteria decision making techniques [5], [10], [15], [18], [21]- [23], [26], [29], [31], [34], [37], [38], [40], [43], fuzzy logic [17], [27], [44], [46], [47], [49], [50], statistical analysis [12], [16], [30], [33], [35], [48], [49], non/linear and mathematical programming [4], [9], [14], [20], [24], [28], [32], [36], [39], [51], heuristic and meta heuristic methods [6], [7], [11], [19], [25], [45] and other decision support systems [8], [13], [23], [41], [42]…”

Section: Discussionmentioning

confidence: 99%

“…ECPD International Conference on Material Handling and Warehousing [8] International Journal of Production Economics [9] IMA Journal of Management Mathematics [10] European Journal of Operational Research [11] European Journal of Operational Research [12] Transportation Research Part E [13] Tunneling and Underground Space Technology [14] European Journal of Operational Research [15] Supply Chain Management: An International Journal [16] International Journal of Business and Management [17] Expert Systems with Applications [18] Journal of Environmental Management [19] Computers & Industrial Engineering [20] Expert Systems with Applications [21] Waste Management [22] Expert Systems with Applications [23] Expert Systems with Applications [24] Doctoral Thesis [25] XI. ISPR [26] Procedia -Social and Behavioral Sciences [27] Interdisciplinary Journal of Contemporary Research in Business [28] Master Thesis [29] Journal Of Industrial Engineering [30] European Planning Studies [31] Computers and Electronics in Agriculture [32] Computers &Operations Research [33] Transportation Research Procedia [34] International Journal of Management Science and Engineering Management [35] Procedia -Social and Behavioral Sciences [36] Computers &Operations Research [37] Advances in Industrial Engineering and Management [38] Decision Science Letters [39] Journal of Social Sciences [40] JEBPIR [41] IFAC-Papers On Line [42] Research in Transportation Economics [43]…”

Section: Studymentioning

confidence: 99%

Literature Review on Success Factors and Methods Used in Warehouse Location Selection

Gergin¹,

Peker²

2019

Pamukkale J Eng Sci

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ÖzThe fact that the production and consumption amounts are different from each other gives a dynamic feature to the concept of storage. In addition, an effective storage activity hinges upon the selection of the right warehouse location that takes into account capital and labor investments; minimizes the transportation cost and time. The aim of this study is to investigate the preliminary researches in the selection of the warehouse location selection and to present information on which success factors and methods are preferred. Within this scope, many academic studies have been examined by filtering various databases. According to the results of the study, the most used methods in warehouse location selection are multi-criteria decision making methods such as AHP, ANP and TOPSIS; and the most commonly used success factor is determined as the cost-based factors. Dünya üzerinde üretim ve tüketim miktarlarının birbirlerinden farklı olması depolama kavramına dinamik bir özellik kazandırmaktadır.Ayrıca etkin bir depolama faaliyeti; sermaye ve işçilik yatırımlarını dikkate alacak, taşıma maliyet ve zamanını minimize edecek doğru depo yerinin seçilmesinden geçmektedir. Bu doğrultuda çalışmanın amacı, depo yeri seçiminde yapılmış olan öncül araştırmaların incelenmesi ve depo yer seçiminde hangi başarı faktörleri ve yöntemlerin tercih edildiğine dair bir bilgi sunmaktır. Bu amaç kapsamında çok sayıda akademik çalışma çeşitli veri tabanları süzülerek incelenmiştir. Çalışmanın sonuçlarına göre depo yer seçiminde en fazla kullanılan yöntemler AHP, ANP ve TOPSIS'in başını çektiği Çok Kriterli Karar Verme yöntemleri, en çok kullanılan başarı faktörü ise Maliyet içerikli faktörler olarak belirlenmiştir.

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“…Simulation-based methods support the optimization of deterministic and stochastic models in the field of transportation [10], collaboration analysis for jointly working members [11], and supply chain optimization to find the core parameters of supply chain strategies to ensure cost efficiency [12]. Decision support systems make it possible to find optimal solutions for resource scheduling in supply chain [13] and group decision-making is an effective tool for facility location problems of supply chains [14].…”

Section: Research On Supply Chainmentioning

confidence: 99%

“…There has recently been an Complexity 3 increased interest in performance analysis of supply chains [1][2][3][4][5][6][7][8][9][10][11][12][13][14] and some recent analysis has been targeted specifically towards the integration of consignment stores into supply chain processes [15][16][17][18][19][20][21] and optimization with metaheuristics based on swarming algorithms [22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40], especially black hole optimization. Firstly, the relevant terms were defined and the initial searches were conducted.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization of Consignment-Store-Based Supply Chain with Black Hole Algorithm

Bányai

Illés

2017

Complexity

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The globalization of economy and market led to increased networking in the field of manufacturing and services. These manufacturing and service processes including supply chain became more and more complex. The supply chain includes in many cases consignment stores. The design and operation of these complex supply chain processes can be described as NP-hard optimization problems. These problems can be solved using sophisticated models and methods based on metaheuristic algorithms. This research proposes an integrated supply model based on consignment stores. After a careful literature review, this paper introduces a mathematical model to formulate the problem of consignment-store-based supply chain optimization. The integrated model includes facility location and assignment problems to be solved. Next, an enhanced black hole algorithm dealing with multiobjective supply chain model is presented. The sensitivity analysis of the heuristic black hole optimization method is also described to check the efficiency of new operators to increase the convergence of the algorithm. Numerical results with different datasets demonstrate how the proposed model supports the efficiency, flexibility, and reliability of the consignment-store-based supply chain.

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Group heterogeneity in multi member decision making model with an application to warehouse location selection in a supply chain

Cited by 63 publications

References 35 publications

A cumulative belief degree approach for group decision‐making problems with heterogeneous information

A cumulative belief degree approach for group decision‐making problems with heterogeneous information

Literature Review on Success Factors and Methods Used in Warehouse Location Selection

Optimization of Consignment-Store-Based Supply Chain with Black Hole Algorithm

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