Picture Fuzzy ARAS Method for Freight Distribution Concept Selection

被引:39
作者
Jovcic, Stefan [1 ]
Simic, Vladimir [2 ]
Prusa, Petr [1 ]
Dobrodolac, Momcilo [2 ]
机构
[1] Univ Pardubice, Fac Transport Engn, Studentska 95, Pardubice 53210, Czech Republic
[2] Univ Belgrade, Fac Transport & Traff Engn, Vojvode Stepe 305, Belgrade 11010, Serbia
来源
SYMMETRY-BASEL | 2020年 / 12卷 / 07期
关键词
picture fuzzy set; ARAS method; multi-criteria decision-making; freight distribution concept; third-party logistics; MULTIPLE CRITERIA ASSESSMENT; ATTRIBUTE DECISION-MAKING; 3RD-PARTY LOGISTICS; SUPPLIER SELECTION; MODEL; AHP; ALTERNATIVES; MANAGEMENT; SETS; ENVIRONMENT;
D O I
10.3390/sym12071062
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Companies can perform their freight distribution in three different ways. The first concept, the in-house concept, represents the use of a company's own resources and knowledge to organize transportation from the production to retailers or from the warehouse to customers. The opposite concept is to outsource distribution activities by hiring third-party logistics providers. The third concept represents a combination of the previous two. Although the arguments in favor of outsourcing can be found in the literature, an appropriate selection of a freight distribution concept is specific for each company and depends on many evaluation criteria and their symmetrical roles. This paper presents a methodology that can be used by companies that need to choose their freight distribution concept. An advanced extension of the Additive Ratio ASsessment (ARAS) method is developed to solve the freight distribution concept selection problem. To illustrate the implementation of the proposed methodology, a tire manufacturing company from the Czech Republic is taken as a case study. However, the proposed picture fuzzy ARAS method is general and can be used by any other company. To validate the novel picture fuzzy ARAS method, a comparative analysis with the nine existing state-of-the-art picture fuzzy multi-criteria decision-making methods is provided.
引用
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页数:23
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