Performance Evaluation of PSO, PSOCA and MPSOCA for Solving University Timetabling Problem

Journal Title: Annals. Computer Science Series - Year 2018, Vol 16, Issue 2

Abstract

In this paper, performance evaluation of Particle Swarm Optimization algorithm (PSO), Particle Swarm Optimization based Cultural Algorithm (PSOCA) and Modified Particle Swarm Optimization based Cultural Algorithm (MPSOCA) was carried out using simulation time, fitness value and number of unallocated courses as performance metrics. The evaluation results of PSO, PSOCA and MPSOCA yielded average simulation times of 35.29, 37.68 and 17.42 seconds, respectively. Also, fitness values of 85, 89 and 90% were recorded for PSO, PSOCA and MPSOCA, respectively. PSO have a total average number of 60 subjects unallocated compare to PSOCA and MPSOCA that successfully allocated all the subjects.

Authors and Affiliations

Oluwaseun M. ALADE, Christopher A. OYELEYE, Oluyinka T. ADEDEJI, Elijah Olusayo Omidiora, Stephen Olatunde Olabiyisi

Keywords

Related Articles

Manual and Fast C Code Optimization

Developing an application with high performance through the code optimization places a greater responsibility on the programmers. While most of the existing compilers attempt to automatically optimize the program code, m...

Image Fusion and Re-Modified SPIHT for Fused Image

This paper presents the Discrete Wavelet based fusion techniques for combining perceptually important image features. SPIHT (Set Partitioning in Hierarchical Trees) algorithm is an efficient method for lossy and lossless...

How many interchanges does the selection sort make for iid geometric(p) input?

The note derives an expression for the number of interchanges made by selection sort when the sorting elements are iid variates from geometric distribution. Empirical results reveal we can work with a simpler model compa...

The Usefulness of Multilevel Hash Tables with Multiple Hash Functions in Large Databases<br />

In this work, attempt is made to select three good hash functions which uniformly distribute hash values that permute their internal states and allow the input bits to generate different output bits. These functions are...

How does the Shift-insertion sort behave when the sorting elements follow a Normal distribution?

The present paper examines the behavior of Shift-insertion sort (insertion sort with shifting) for normal distribution inputs and is in continuation of our earlier work on this new algorithm for discrete distribution inp...

Download PDF file
  • EP ID EP550307
  • DOI -
  • Views 102
  • Downloads 0

How To Cite

Oluwaseun M. ALADE, Christopher A. OYELEYE, Oluyinka T. ADEDEJI, Elijah Olusayo Omidiora, Stephen Olatunde Olabiyisi (2018). Performance Evaluation of PSO, PSOCA and MPSOCA for Solving University Timetabling Problem. Annals. Computer Science Series, 16(2), 149-154. https://europub.co.uk/articles/-A-550307