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

Aderemi Oluyinka Adewumi () and Peter Ayokunle Popoola
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Aderemi Oluyinka Adewumi: University of KwaZulu-Natal
Peter Ayokunle Popoola: University of KwaZulu-Natal

International Journal of System Assurance Engineering and Management, 2018, vol. 9, issue 1, No 13, 98-110

Abstract: Abstract 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.

Keywords: Discrete particle swarm optimization; Submission decision process; Multi-objective optimization (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s13198-016-0487-2

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