Research Article Open Access

Ant Colony Optimization for Load Management Based on Load Shifting in the Textile Industry

Chaimongkon Chokpanyasuwan1, Tika Bunnag2 and Ratthasak Prommas3
  • 1 Rattanakosin College for Sustainable Energy and Environment (RCSEE), Rajamangala University of Technology Rattanakosin, 96 moo 3 Puthamonthon Sai 5, Salaya, Puthamonthon, Nakhon Pathom, 73170, Thailand
  • 2 Pitipak Engineering Co., Ltd. 508 /12 Carpark Building Synphaet Hospital Ramindra Rd, Ramindra, Kannayaw 10230, Thailand
  • 3 Department of Mechanical Engineering, Faculty of Engineering, Rajamangala University of Technology Rattanakosin, (RMUTR), 96 moo 3 Puthamonthon Sai 5, Salaya, Puthamonthon, Nakhon Pathom, 7317, Thailand

Abstract

The textile industry is a complicated manufacturing industry because it is a fragmented and heterogeneous sector dominated by Small and Medium Enterprises (SMEs). There are various energy-efficiency opportunities that exist in every textile plant. However, even cost-effective options often are not implemented in textile plants mostly because of limited information on how to implement energy-efficiency measures. This paper presents the expansion of problem formulation of consummation management based on load shifting in textile industry. The mathematical model is a Non Polynomial (NP) hard optimization problem to determine the start time of the process in order to minimize the total electricity cost under varying tariffs such as flat rate and Time of Use (TOU). For solve this problem, Ant Colony Optimization (ACO) is applied and compared with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). To show its efficiency, the case studies in case of Single Process Multiple Jobs (SPMJ) in term of small, medium and large scales are demonstrated.  The results show that the proposed method is able to achieve the best solution efficiently and easy to implement.

American Journal of Applied Sciences
Volume 12 No. 2, 2015, 142-154

DOI: https://doi.org/10.3844/ajassp.2015.142.154

Submitted On: 20 November 2014 Published On: 9 April 2015

How to Cite: Chokpanyasuwan, C., Bunnag, T. & Prommas, R. (2015). Ant Colony Optimization for Load Management Based on Load Shifting in the Textile Industry. American Journal of Applied Sciences, 12(2), 142-154. https://doi.org/10.3844/ajassp.2015.142.154

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Keywords

  • Load Management
  • Time of Use
  • Ant Colony Algorithm
  • Textile Industry Optimization