Improving Optimization Solution for Facility Layout Problem with Thermal Comfort

Authors

  • Noorhadila Mohd Bakeri School of Technology Management and Logistic, College of Business, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Mohd Faizal Omar School of Quantitative Sciences, College of Arts and Sciences, 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
  • Faizal Baharum School of Housing, Building and Planning, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia

Keywords:

Facility Layout Problem, thermal comfort, meta-heuristic algorithm

Abstract

Facility Layout Problem (FLP) can be considered as a classical problem in quantitative studies. However, the literature in FLP are largely neglected the thermal comfort as part of the objective function. Today, energy savings for buildings are a major concern in the world as they cover a big portion of energy use. The public room consumes high energy use because of its ability to occupy many people at one time. Issues arise when each person has a dissimilar thermal satisfaction rate, while each area in a room provides a different temperature. There are many factors that influence the people dispersion in the room including the facility layout. However, it is really testing to handle an air-conditioning control () system by considering the mention factors to ensure the thermal satisfaction is increased and energy is reduced. Since lack of report on thermal factors in Facility Layout Problem (FLP) area, this work aims to optimize the temperature setting of an  system at the best point and achieving the finest plan for the facility layout in a room. Further, our ultimate goals to maximize the thermal comfort level and reduce energy consumption are able to accomplish. A non-linear mathematical model is utilized to optimize the thermal satisfaction rate () and room layout. At the end of the article, we proposed an Evolutionary Algorithm (EA) to find a quality solution or near optimal since it is hard to solve this problem in a reasonable time.

Published

2021-07-20
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