Intuitionistic Fuzzy Hub Location Problems: Model and Solution Approach

IF 1.3 Q2 MATHEMATICS, APPLIED
M. Niksirat
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引用次数: 1

Abstract

One of the most important problems in network design applications is the hub location problem, which is an extension of the facility location problem. The purpose of the problem is to select the least hub nodes from the available nodes so by establishing faster connections between hub nodes, the cost of transferring the entire network traffic is minimised. To deal with uncertainty and hesitation, the traffic amount between origin and destination nodes, the transfer cost, and the cost of establishing hub nodes are considered to be trapezoidal intuitionistic fuzzy numbers. The problem is formulated, and a new approach and a linearisation technique are shown to transform the Intuitionistic Fuzzy Hub Location Problem into a classical one. The transformed problem is solved using integer linear programming algorithms. The feasibility and efficiency of the obtained solutions applied to some airline passenger distribution problem applications are illustrated.
直觉模糊轮毂定位问题:模型与求解方法
枢纽选址问题是网络设计应用中最重要的问题之一,它是设施选址问题的延伸。该问题的目的是从可用节点中选择最少的集线器节点,以便通过在集线器节点之间建立更快的连接,将传输整个网络流量的成本降至最低。为了处理不确定性和犹豫性,将起点和目的地节点之间的交通量、转移成本和建立枢纽节点的成本考虑为梯形直觉模糊数。提出了一种新的方法和线性化技术,将直觉模糊轮毂定位问题转化为经典轮毂定位问题。用整数线性规划算法求解变换后的问题。最后,将所得解应用于某航空公司客流分配问题的可行性和有效性进行了说明。
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
13
审稿时长
40 weeks
期刊介绍: Fuzzy Information and Engineering—An International Journal wants to provide a unified communication platform for researchers in a wide area of topics from pure and applied mathematics, computer science, engineering, and other related fields. While also accepting fundamental work, the journal focuses on applications. Research papers, short communications, and reviews are welcome. Technical topics within the scope include: (1) Fuzzy Information a. Fuzzy information theory and information systems b. Fuzzy clustering and classification c. Fuzzy information processing d. Hardware and software co-design e. Fuzzy computer f. Fuzzy database and data mining g. Fuzzy image processing and pattern recognition h. Fuzzy information granulation i. Knowledge acquisition and representation in fuzzy information (2) Fuzzy Sets and Systems a. Fuzzy sets b. Fuzzy analysis c. Fuzzy topology and fuzzy mapping d. Fuzzy equation e. Fuzzy programming and optimal f. Fuzzy probability and statistic g. Fuzzy logic and algebra h. General systems i. Fuzzy socioeconomic system j. Fuzzy decision support system k. Fuzzy expert system (3) Soft Computing a. Soft computing theory and foundation b. Nerve cell algorithms c. Genetic algorithms d. Fuzzy approximation algorithms e. Computing with words and Quantum computation (4) Fuzzy Engineering a. Fuzzy control b. Fuzzy system engineering c. Fuzzy knowledge engineering d. Fuzzy management engineering e. Fuzzy design f. Fuzzy industrial engineering g. Fuzzy system modeling (5) Fuzzy Operations Research [...] (6) Artificial Intelligence [...] (7) Others [...]
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