Methodology for Modified Whale Optimization Algorithm for Solving Appliances Scheduling Problem

Authors

  • Mohd Faizal Omar School of Quantitative Sciences, College of Arts and Sciences, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Noorhadila Mohd Bakeri School of Technology Management and Logistic, College of Business, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Mohd Nasrun Mohd Nawi School of Technology Management and Logistic, College of Business, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Norfazlirda Hairani Faculty of Entrepreneurship and Business, Universiti Malaysia Kelantan, 16100 Pengkalan Chepa, Kelantan, Malaysia
  • Khalizul Khalid Faculty of Management and Economics, Sultan Idris Education University, 35900 Tanjung Malim, Perak, Malaysia

DOI:

https://doi.org/10.37934/arfmts.76.2.132143

Keywords:

Scheduling Problem, Swarm Intelligence, Whale Optimization Algorithm

Abstract

Whale Optimization Algorithm (WOA) is considered as one of the newest metaheuristic algorithms to be used for solving a type of NP-hard problems. WOA is known of having slow convergence and at the same time, the computation of the algorithm will also be increased exponentially with multiple objectives and huge request from n users. The current constraints surely limit for solving and optimizing the quality of Demand Side Management (DSM) case, such as the energy consumption of indoor comfort index parameters which consist of thermal comfort, air quality, humidity and vision comfort. To address these issues, this proposed work will firstly justify and validate the constraints related to the appliances scheduling problem, and later proposes a new model of the Cluster based Multi-Objective WOA with multiple restart strategy. In order to achieve the objectives, different initialization strategy and cluster-based approaches will be used for tuning the main parameter of WOA under different MapReduce application which helps to control exploration and exploitation, and the proposed model will be tested on a set of well-known test functions and finally, will be applied on a real case project i.e. appliances scheduling problem. It is anticipating that the approach can expedite the convergence of meta-heuristic technique with quality solution.

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Published

2020-10-23

How to Cite

Omar, M. F., Mohd Bakeri, N., Mohd Nawi, M. N., Hairani, N., & Khalid, K. (2020). Methodology for Modified Whale Optimization Algorithm for Solving Appliances Scheduling Problem. Journal of Advanced Research in Fluid Mechanics and Thermal Sciences, 76(2), 132–143. https://doi.org/10.37934/arfmts.76.2.132143

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Section

Articles