School of Science and Technology 科技學院
Computing Programmes 電腦學系
| Programme | Bachelor of Computing with Honours in Internet Technology |
| Supervisor | Dr. Vanessa Ng |
| Areas | Algorithms |
| Year of Completion | 2017 |
| Award Received | Champion, IEEE Computational Intelligence Chapter FYP Competition 2017 |
Three objectives were carried out to come up with the project. First, introduce hybrid paradigms of Two Phase local search (TPLS) and multi-objective ant colony optimization (MOACO). Second, implement the Iterated Local Search – Variable Neighborhood Search (ILS-VNS) as the first phase in TPLS; and then, to investigate the performance of proposed algorithm with different settings of local search choice and population size. To specify, comparison of choice of TPLS using with WLS and PLS is also considered. A statistical testing will be carried out to evaluate the significance of the result. More importantly, further analyze on population size effect on solution archive size and performance.
Accord to Dubois (Dubois-Lacoste et al., 2013), noted there is two main approaches of optimization, scalarization-based method and dominance-based method are the ways the algorithm finding solutions.
Scalarization-based method
Dominance-based method
Furthermore, he described these two approaches can come into a hybridization. The hybridization can be done with either one or both paradigm instances described above. Two categories of hybridization techniques were presented.
Sequential hybridization
Iterative hybridization
Figure 1: TPLS + PLS + MOACO Framework
Figure 2: MOACO + TPLS
In this project, MOACO were further enhanced with a state-of-art approach. A hybridization of Two Phase Local Search and Multi-Objective Ant Colony Optimization was introduced. To improve the initial solution for MOACO, Two Phase Local Search were proposed to combine with MOACO. To aim at a higher quality of supported efficient solution set as the initial solution, Iterated Local Search – Variable Neighborhood Search is proposed. A series of experimental testing examined the performance of algorithms for Bi-objective Traveling Salesman Problem. Several performance indicator and statistical testing were adopted to investigate and verify the significance of the result. The result had shown the proposed algorithm TPLS + PLS + MOACO outperformed the conventional algorithm. More importantly, the population size setting was also compared to test the best parameter. The result was shown S_size=100 perform the best averagely on TPLS + PLS + MOACO.
In future, the proposed algorithm can be investigated more concisely with its intrinsic components. For instance, testing the algorithmic components of PLS, as the author did in the paper (Dubois-Lacoste, 2011). On the other hand, the restarting strategy in the first phase of TPLS could be improved rather than restart from a random solution. Also, stop condition for ILS-VNS could be analyzed in detail to generate a better solution within a shorter time.
Jonathan handles all external affairs include business development, patents write up and public relations. He is frequently interviewed by media and is considered a pioneer in 3D printing products.
After graduating from OUHK, Krutz obtained an M.Sc. in Engineering Management from CityU. He is now completing his second master degree, M.Sc. in Biomedical Engineering, at CUHK. Krutz has a wide range of working experience. He has been with Siemens, VTech, and PCCW.
Hugo Leung Wai-yin, who graduated from his four-year programme in 2015, won the Best Paper Award for his ‘intelligent pill-dispenser’ design at the Institute of Electrical and Electronics Engineering’s International Conference on Consumer Electronics – China 2015.
The pill-dispenser alerts patients via sound and LED flashes to pre-set dosage and time intervals. Unlike units currently on the market, Hugo’s design connects to any mobile phone globally. In explaining how it works, he said: ‘There are three layers in the portable pillbox. The lowest level is a controller with various devices which can be connected to mobile phones in remote locations. Patients are alerted by a sound alarm and flashes. Should they fail to follow their prescribed regime, data can be sent via SMS to relatives and friends for follow up.’ The pill-dispenser has four medicine slots, plus a back-up with a LED alert, topped by a 500ml water bottle. It took Hugo three months of research and coding to complete his design, but he feels it was worth all his time and effort.
Hugo’s public examination results were disappointing and he was at a loss about his future before enrolling at the OUHK, which he now realizes was a major turning point in his life. He is grateful for the OUHK’s learning environment, its industry links and the positive guidance and encouragement from his teachers. The University is now exploring the commercial potential of his design with a pharmaceutical company. He hopes that this will benefit the elderly and chronically ill, as well as the society at large.
Soon after completing his studies, Hugo joined an automation technology company as an assistant engineer. He is responsible for the design and development of automation devices. The target is to minimize human labor and increase the quality of products. He is developing products which are used in various sections, including healthcare, manufacturing and consumer electronics.
| Course Code | Title | Credits | |
|---|---|---|---|
| COMP S321F | Advanced Database and Data Warehousing | 5 | |
| COMP S333F | Advanced Programming and AI Algorithms | 5 | |
| COMP S351F | Software Project Management | 5 | |
| COMP S362F | Concurrent and Network Programming | 5 | |
| COMP S363F | Distributed Systems and Parallel Computing | 5 | |
| COMP S382F | Data Mining and Analytics | 5 | |
| COMP S390F | Creative Programming for Games | 5 | |
| COMP S492F | Machine Learning | 5 | |
| ELEC S305F | Computer Networking | 5 | |
| ELEC S348F | IOT Security | 5 | |
| ELEC S371F | Digital Forensics | 5 | |
| ELEC S431F | Blockchain Technologies | 5 | |
| ELEC S425F | Computer and Network Security | 5 |
| Course Code | Title | Credits | |
|---|---|---|---|
| ELEC S201F | Basic Electronics | 5 | |
| IT S290F | Human Computer Interaction & User Experience Design | 5 | |
| STAT S251F | Statistical Data Analysis | 5 |
| Course Code | Title | Credits | |
|---|---|---|---|
| COMPS333F | Advanced Programming and AI Algorithms | 5 | |
| COMPS362F | Concurrent and Network Programming | 5 | |
| COMPS363F | Distributed Systems and Parallel Computing | 5 | |
| COMPS380F | Web Applications: Design and Development | 5 | |
| COMPS381F | Server-side Technologies and Cloud Computing | 5 | |
| COMPS382F | Data Mining and Analytics | 5 | |
| COMPS390F | Creative Programming for Games | 5 | |
| COMPS413F | Application Design and Development for Mobile Devices | 5 | |
| COMPS492F | Machine Learning | 5 | |
| ELECS305F | Computer Networking | 5 | |
| ELECS363F | Advanced Computer Design | 5 | |
| ELECS425F | Computer and Network Security | 5 |
