Open AccessImproved artificial bee colony algorithm for air freight station scheduling
Author(s) -
Haiquan Wang,
HansDietrich Haasis,
Menghao Su,
Jianhua Wei,
Xiaobin Xu,
Shengjun Wen,
Juntao Li,
Wenxuan Yue
Publication year - 2022
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2022607
Subject(s) - scheduling (production processes) , computer science , mathematical optimization , job shop scheduling , artificial bee colony algorithm , operations research , routing (electronic design automation) , engineering , artificial intelligence , mathematics , computer network
Aiming at improving the operating efficiency of air freight station, the problem of optimizing the sequence of inbound/outbound tasks meanwhile scheduling the actions of elevating transfer vehicles (ETVs) is discussed in this paper. First of all, the scheduling model in airport container storage area, which considers not only the influence of picking sequence, optimal ETVs routing without collision, but also the assignment of input and output ports, is established. Then artificial bee colony (ABC) is proposed to solve the above scheduling issue. For further balancing the abilities of exploration and exploitation, improved multi-dimensional search (IMABC) algorithm is proposed where more dimensions will be covered, and the best dimension of the current optimal solution is used to guide the evolutionary direction in the following exploitation processes. Numerical experiments show that the proposed method can generate optimal solution for the complex scheduling problem, and the proposed IMABC outperforms original ABC and other improved algorithms.