CHAPTER 6 CONCLUSIONS AND FUTURE STUDIES
6.2 Future Studies
For further research, we will attempt to apply our PSO to other shop scheduling problems with multiple objectives. Possible topics for further study include the modification of particle position representation, particle movement, and particle velocity. In addition, issues related to Pareto optimal such as solution maintenance strategy and performance measurement are also worth to be investigated in future.
We will also attempt to apply MOPSO to other shop scheduling problems with multiple objectives in future research. Other possible topics for further study include modification of the particle position, particle movement, and particle velocity
representation. Issues related to Pareto optimization, such as solution maintenance strategy and performance measurement, also merit future investigation.
Appendix
The pseudo-code of the PSO for MO-FSSP is as follow.
Initialize a population of particles with random positions.
for each particle k do
Evaluate Xk(the position of particle k) Save the pbestk to optimal solution set S end for
Set gbest solution equals to the best pbestk repeat
Updates particles velocities for each particle k do
Move particle k Evaluate Xk
Update gbest, pbest and S end for
until maximum iteration limit is reached
The pseudo code of the PSO for MO-JSSP is given below:
Initialize a population of particles with random positions.
for each particle k do
Apply G&T algorithm to decode X into a schedule k S . k set the kth pbest solution (pbestk) equal to S , k pbest ←k S . k end for
set gbest solution equal to the best pbestk. repeat
update velocities for each particle k do
move particle k
apply G&T algorithm to decode x into k S . k update pbest solutions and gbest solution end for
until maximum iterations is attained
The pseudo code of the PSO for MO-OSSP is given below:
Initialize a population of particles with random positions.
for each particle k do
Apply G&T algorithm to decode X into a schedule k S . k set the kth pbest solution (pbestk) equal to S , k pbestk←S . k end for
set gbest solution equal to the best pbestk.
repeat
update velocities for each particle k do
move particle k
apply G&T algorithm to decode x into k S . k update pbest solutions and gbest solution end for
until maximum iterations is attained
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作者簡介
姓名：林信宏 (Hsing-Hung Lin) 學歷：
學士 東海大學 資訊科學系 (79.9~83.6) 碩士 中華大學 工業工程與管理研究所 (85.9~87.6) 博士 交通大學 工業工程與管理研究所 (93.9~ 99.6)
著作：
一、 期刊論文
1. D.Y. Sha, Hsing-Hung Lin, 2009, “A particle swarm optimization for multi-objective flowshop scheduling,” International Journal of Advanced Manufacturing Technology, 45(7), 749-762. (SCI)
2. D.Y. Sha, Hsing-Hung Lin, 2010, “A multi-objective PSO for job-shop scheduling problem,” Expert Systems with Applications, 37(2), 1065-1070. (SCI)
二、 審查中論文
1. D.Y. Sha, Hsing-Hung Lin, “A multi-objective PSO for open-shop scheduling problem,” submit to Journal of Information & Optimization Sciences
2. D.Y. Sha, Hsing-Hung Lin, “A novel particle swarm optimization for multi-objective job-shop scheduling ,” submit to Journal of Industrial and Management Optimization
3. D.Y. Sha, Hsing-Hung Lin, “Scheduling multi-objective jobshops using particle swarm optimization,” submitted to Journal of Intelligent Manufacturing
三、 研討會論文
1. D.Y. Sha, Hsing-Hung Lin, 2008, “A Multi-objective Particle Swarm Optimization for Flow Shops Scheduling Problem,” Proceedings of the 38th International Conference on Computers and Industrial Engineering, pp. 233-241, Beijing, China.
2. D.Y. Sha, Hsing-Hung Lin, 2008, “A Pareto Archive Particle Swarm Optimization for Multi-objective Flowshop Scheduling,” Proceedings of the
2008 Asia Pacific Industrial Engineering & Management Systems Conference, pp.2269-2277, Bali, Indonesia.
3. D.Y. Sha, Hsing-Hung Lin, 2009, “A Multi-objective PSO for Job-shop Scheduling Problem,” Proceedings of the 39th International Conference on Computers and Industrial Engineering, Troyes, France.
4. D.Y. Sha, Hsing-Hung Lin, 2009, “A Novel Particle Swarm Optimization for Multi-objective Job-shop Scheduling,” Proceedings of the 2009 Asia Pacific Industrial Engineering & Management Systems Conference, Kitakyushu, Japan.
5. D.Y. Sha, Hsing-Hung Lin, 2010, “A Modified Particle Swarm Optimization for Multi-objective Open-shop Scheduling,” Proceedings of the 2010 AENG International Conference on Industrial Engineering, Hong Kong.