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A hybrid indicator many‐objective optimization algorithm for the selection and delivery of disaster relief materials problem
Author(s) -
Zhu Zhuanghua
Publication year - 2020
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5948
Subject(s) - benchmark (surveying) , selection (genetic algorithm) , computer science , mathematical optimization , emergency management , emergency relief , optimization problem , optimization algorithm , operations research , algorithm , engineering , mathematics , artificial intelligence , law , geography , geodesy , political science
Traditional methods fail to comprehensively consider the selection and delivery of disaster relief materials (SDDM) problem. To solve the problem, the SDDM will be comprehensively considered in this article, which will be built into a many‐objective disaster relief materials selection and delivery model with four objectives to be optimized in the last kilometer of the disaster relief organization. Meanwhile, a many‐objective optimization algorithm is designed to solve the proposed disaster relief materials model by employing the different excellent indicators. Two extensive simulation experiments are carried out. On the one hand, the performance of the designed many‐objective is tested on DTLZ and WFG benchmark functions. On the other hand, the proposed many‐objective model is solved by employing the designed algorithm. In addition, the simulation result shows that the designed algorithm is effective in solving the SDDMs problem.