Fuzzy-Control-Based Chance-Constrained Programming for Humanitarian Relief Allocation Problem

被引：2
作者：
Zhang, Jianghua [1 ]
Liu, Yang [1 ]
Su, Xiaojie [2 ]
Shi, Peng [3 ]
机构：
[1] Shandong Univ, Sch Management, Jinan 250100, Peoples R China
[2] Chongqing Univ, Coll Automat, Chongqing 400044, Peoples R China
[3] Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, Australia
来源：
IEEE TRANSACTIONS ON FUZZY SYSTEMS | 2022年 / 30卷 / 06期
基金：
中国国家自然科学基金;
关键词：
Resource management; Transportation; Stochastic processes; Uncertainty; Fuzzy control; Logistics; Optimization; fuzzy number; humanitarian rescue; resource allocation; STOCHASTIC OPTIMIZATION; MODEL; FRAMEWORK; LOCATION; SYSTEMS;
D O I：
10.1109/TFUZZ.2021.3073474
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this article, the issue of multicenter and single-area humanitarian relief allocation with uncertain travel time and imprecise transportation information is investigated. Expert human knowledge using fuzzy control is employed to select rescue paths, and the considered problem is formulated as a fuzzy chance-constrained model to ensure that the allocated goods can be delivered to the disaster area on time within a desired probability. A new method is presented to transform chance-constrained programming into a mixed-integer model utilizing triangle fuzzy numbers and the robust optimization problem. A practical example is used to test the validity of the theoretic results obtained.
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页码：2044 / 2054
页数：11
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