A multi-objective particle swarm optimization for the submission decision process

被引：4
作者：
Adewumi A.O. [1 ]
Popoola P.A. [1 ]
机构：
[1] Applied Artificial Intelligence Research Unit, School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Durban
来源：
International Journal of System Assurance Engineering and Management | 2018年 / 9卷 / 1期
关键词：
Discrete particle swarm optimization; Multi-objective optimization; Submission decision process;
D O I：
10.1007/s13198-016-0487-2
中图分类号：
学科分类号：
摘要：
The recently introduced Submission Decision Process problem entails deciding, out of N-1! possible journal submission schedules, which one will, if followed, give an author the maximum expected number of citations while minimizing the expected number of submissions required on one hand, or the expected time spent in review on the other hand. The unnecessarily high computational burden in the existing algorithm used for addressing this problem was observed, and propose a new discrete Multi-Objective Particle Swarm Optimization algorithm which cuts down computational time by a huge factor is proposed. An improvement in the computation of the various objectives is also suggested which further reduces computational burden, and the problem is extended beyond the usual bi-objective optimization to a 3-objective optimization which is solved with the proposed algorithm. © 2016, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.
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收藏
页码：98 / 110
页数：12
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