Work place: Faculty of Engineering and Technology, Panyapiwat Institute of Management, Nonthaburi, Thailand
Research Interests: Chemistry & Materials Science, Materials Science
Waraporn Klinbun (1983 －), female, Bangkok, Thailand, supervisor for Ph.D. candidate, she received a bachelor degree in Biotechnology, Master and Ph.D. degree in Mechanical Engineering from Thammasat University, Thailand. Her research focuses on the electromagnetic energy analysis in various fields, including heating and drying process, microwave technology, transportation phenomena by using computational fluid dynamic method such as finite volume. Her works are well received internationally and have been presented and published in the first and second tier conferences and journals.
Research areas that she currently focuses on are the analysis of mathematical modeling of various processes related to electromagnetic heating of dielectric materials, transportation in porous media, including bioengineering process.
DOI: https://doi.org/10.5815/ijmecs.2014.05.05, Pub. Date: 8 May 2014
The adaptive current search (ACS) is one of the novel metaheuristic optimization search techniques proposed for solving the combinatorial optimization problems. This paper aimed to present the application of the ACS to optimize the real-world traveling transportation problems (TTP) of a specific car factory. The total distance of the selected TTP is performed as the objective function to be minimized in order to decrease the vehicle’s energy. To perform its effectiveness, four real-world TTP problems are conducted. Results obtained by the ACS are compared with those obtained by genetic algorithm (GA), tabu search (TS) and current search (CS). As results, the ACS can provide very satisfactory solutions superior to other algorithms. The minimum total distance and the minimum vehicle’s energy of all TTP problems can be achieved by the ACS with the distant error of no longer than 3.05%.[...] Read more.
DOI: https://doi.org/10.5815/ijisa.2014.03.01, Pub. Date: 8 Feb. 2014
This paper aims to apply a modified current search method, adaptive current search (ACS), for assembly line balancing problems. The ACS algorithm possesses the memory list (ML) to escape from local entrapment and the adaptive radius (AR) mechanism to speed up the search process. The ACS is tested against five benchmark unconstrained and three constrained optimization problems compared with genetic algorithm (GA), tabu search (TS) and current search (CS). As results, the ACS outperforms other algorithms and provides superior results. The ACS is used to address the number of tasks assigned for each workstation, while the heuristic sequencing (HS) technique is conducted to assign the sequence of tasks for each workstation according to precedence constraints. The workload variance and the idle time are performed as the multiple-objective functions. The proposed approach is tested against four benchmark ALB problems compared with the GA, TS and CS. As results, the ACS associated with the HS technique is capable of producing solutions superior to other techniques. In addition, the ACS is an alternative potential algorithm to solve other optimization problems.[...] Read more.
Subscribe to receive issue release notifications and newsletters from MECS Press journals