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职场能力评价定义
Operation Research / Machine Learning / Algorithm / Optimization Modeling
• Cultivated with statistical learning, artificial Intelligence, linear programming, production and manufacturing management and other quantitative reasoning fields.
• Work on and Explore occupations related to algorithms, combinatorics and optimization.
• Eager to explore and analyze data to support business finding potential knowledge and insight through optimization technique and data analysis method
A resourceful operation analyst with sharp quantitative and programming skills possesses 3-year experience deal with optimization problem in Semiconductor Company, TFT-LCD Panel Industry, specialty memory IC company, printed circuit board (PCB) industry, and Electronic Assembly Manufacturer.
Here's my LinkedIn, Personal Web, mail and GitHub
Advanced Skills
Programming Language
Familiar with Object Oriented Programming(C++, Java, C#) and other high-level programming language including R, Python and Excel VBA.
Operation Research
An optimal analyst possesses 3-year experience deal with optimization problem.
Work on and Explore occupations related to algorithms, combinatorics and optimization.
Machine Learning
Apply reinforcement learning framework to optimization problem with high complexity, huge size and complicated constraints.
Focus on MCTS, optimization theory, reinforcement learning and statistical techniques.
Optimization Programming
• Build a tree-based reinforcement learning optimization algorithm applying ensemble dispatching rules and Monte Carlo Tree Search (MCTS) to solve scheduling problems with huge size under short time constraints /* Patent ID : TWI633504 */
• Develop a heuristic algorithm method(Lagrangian relaxation method) to solve scheduling problem in a large scale for searching a good solution in an effective way.
• Develop a integrated system contains efficient meta-heuristics algorithm such as GA, PSO with Chaos-based initialization, ACO and AFSA(Artificial Fish-Swarm Algorithm) to solve classic benchmark including TSP, assignment problem and bin packing problem.
• Experienced in linear programming language such as OOP with Lingo / Cplex package.
• Build a fuzzy inference system contains 10+ membership function in C#.
• Implement Back Propagation Neural Network in C#.
工作經歷
Industrial Technology Research Institute (ITRI)(工業技術研究院, 工研院), Data Analyst & Optimization Analyst (2nd year), Dec 2017 ~ 現在
Focused on reinforcement learning, statistics method and optimization techniques
• Built model to simulate Photolithography & Patterning System and optimize its production schedule. Raise 6.9% PoH(pieces per hour) in 70% cases, 3.75% on average. Total computation time required is less than 5 min. The expected revenue earned is over 50 million (DRAM Devices Industry)
• Developed batching scheduling algorithm and setup a flexible 3-D data structure to storage highly varying scheduling data in small-volume, large-variety production system. Increase 11% order fill rate and reduce 20% computing time (Printed Circuit Board (PCB) Industry)
• Designed dispatching rules to solve mass production scheduling problem with huge size(30000+ jobs and 100+ machines) in 10 minutes. Implement divide and conquer algorithm to saved 80%+ computation time and meet 99% utilization (TFT-LCD Panels Industry)
Industrial Technology Research Institute (ITRI)(工業技術研究院, 工研院), Data Analyst & Optimization Analyst (1st year), Dec 2016 ~ Dec 2017
Intelligent Analytic Tech. Div - Data Analytic Tech. Dept
• Built a tree-based reinforcement learning optimization algorithm applying ensemble dispatching rules and Monte Carlo Tree Search (MCTS) to solve scheduling problems with huge size under short time constraints /* Patent ID : TWI633504 */
• Developed Intelligent Scheduling Technology to solve complicated combination problem and ensured projects were delivered on or ahead of schedule
- Set up the Tree-based Scheduling Algorithm to optimize the schedule problem under many constraints and achieve the required objective(min makespan/WIP/...)
- Built related module in scheduling problems such as batching process, mask transportation, preserving maintenance, out sourcing, reticle sharing, unexpected crash, machine setup and yield issue
• Developed an algorithm to analyze workload of manufacturing system by statistical theory and unsupervised clustering method
LMPMARKET PTE. LTD., Singapore, Partner and Optimization Analyst, Dec 2018 ~ 現在
• Building the programming solver to generate best supply strategy by considering elasticity of capacity between electricity spot market and power generator with long term contractual commitments. Work with Dr. Yen-Shong Chiao, Singapore
• Maintaining programming model to ensure that current solver meets customer needs and constraints
LMPMARKET PTE. LTD., Singapore, Optimization Analyst and Algorithm Programmer, May 2017 ~ Dec 2018
• Power Network Planning and Optimization
- Built and modified the Linear Programming Model to represent a Electric Power Network System
- Solved the problem and determine optimal electric power supply strategy based on known demand and capacity in Java(with Lingo Package)
• Searched for potential strategy to improve transporting strategy by sensitivity analysis and constraints relaxation
- (Seller) Find best power transmission strategy to maximize revenue(at lowest transportation loss)
- (Buyer) Find best transaction strategy to minimize cost(result from price differences of many power generators between different areas)
Industrial Technology Research Institute (ITRI)(工業技術研究院, 工研院) Research Intern - Machine Learning Project, Mar 2015 ~ Dec 2015
• Built a unsupervised clustering model, including hierarchical algorithm(HA) and k-means clustering, to analysis complex time series of indicator, for example, PM10 and PM2.5 concentrations at Taiwan based on data from Taiwan Air Quality Monitoring Network
• Visualized the air quality data by statistical techniques and plot results in R language
• Compared the common machine learning algorithms, including support vector machine, neural network, decision tree, radon forest and so on in various data set in R language in order to realize the characteristic of each algorithm, and organized into technical documents
• Built the simulation model about traffic system for the demonstration of application in data analytic in Java
Cloud Farm, Product Manager, Jun 2012 ~ Jul 2014
Project planning, Web Database Development and Marketing
• Design the MVC(Model–view–controller) architecture of system, and implement the database design and web programming
• Arranged harvesting schedule by considering the planting time, demand and due date of order. Responsible for daily logistics management and shipping
• In charge of sale and communicate with customers, acknowledging of orders and hold the customer complaints
• Lead a team of 8 people and successfully develop e-commerce and business model to expanse distribution channel of local agriculture, increasing 15% of retail revenue
• Analyze the planting process, transforming to manufacturing structure to build food traceability by ERP(Enterprise Resource Planning)
• Target and connect to potential customers who are likely to bulk order and help farmer pricing products, eventually winning the 5 cases of companies order with 200+ carton of agricultural products
Publications
Conference Papers
- Che-Ming Kuo, Heuristic Algorithm for Scheduling of Make-to-Order Plant Factory with Considering Crops Size Variation during Cultivation, Chinese Institute of Industrial Engineers Annual Conference(CIIE2015).
- Kwei-Long Huang, Chao-Lung Yang, Che-Ming Kuo*(corresponding author) and Hao-Chen Weng, A Plant Factory Scheduling Research with Multi-Period Harvest, The 17th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS 2016).
- A Scheduling Research in Plant Factory with Considering Multi-Period Harvest, 2016
- Tsung-Jung Hsieh, Sen-Chia Chang, Yao-Chung Hsu, Che-Ming Kuo, I-Hsuan Chung, Tree Search-Based Scheduling Method and An Apparatus Using the Same (TW I633504B)
學歷
National Taiwan University, 科學碩士（MS）, Industrial Engineering, 2015 ~ 2016
Master Thesis : A Scheduling Research in Plant Factory with Considering Multi-Period Harvest
This study focus on the crop-scheduling problem for a plant factory and consider the special property of crops which can be harvested multiple times. This scheduling problem is formulated as a mixed integer programming (MIP) problem.
The objective function is defined as to find the maximum revenue for the plant factory under the consider of different practical condition including types of crops, cultivation room number, cultivation room space, heterogeneous harvesting amount among different environment of cultivation room and multiple harvesting period.
This study develops a heuristic algorithm method(Lagrangian relaxation method) to solve scheduling problem in a large scale for searching a good solution(gap is less than 20%) in an effective way(reduce 90%+ computing time).
National Taiwan University of Science and Technology, 科學碩士（MS）, Industrial Management, 2014 ~ 2015
Attended, earning 20+ credits in manufacturing, artificial intelligence and algorithm field, and transfer to Nation Taiwan University to got an MS in Industrial Engineering.
National Yunlin University of Science and Technology, 工學學士（BEng）, Industrial Engineering and Management, 2010 ~ 2014
Graduating in the honor of the first lead.
Operation Research / Machine Learning / Algorithm / Optimization Modeling
• Cultivated with statistical learning, artificial Intelligence, linear programming, production and manufacturing management and other quantitative reasoning fields.
• Work on and Explore occupations related to algorithms, combinatorics and optimization.
• Eager to explore and analyze data to support business finding potential knowledge and insight through optimization technique and data analysis method
A resourceful operation analyst with sharp quantitative and programming skills possesses 3-year experience deal with optimization problem in Semiconductor Company, TFT-LCD Panel Industry, specialty memory IC company, printed circuit board (PCB) industry, and Electronic Assembly Manufacturer.
Here's my LinkedIn, Personal Web, mail and GitHub
Advanced Skills
Programming Language
Familiar with Object Oriented Programming(C++, Java, C#) and other high-level programming language including R, Python and Excel VBA.
Operation Research
An optimal analyst possesses 3-year experience deal with optimization problem.
Work on and Explore occupations related to algorithms, combinatorics and optimization.
Machine Learning
Apply reinforcement learning framework to optimization problem with high complexity, huge size and complicated constraints.
Focus on MCTS, optimization theory, reinforcement learning and statistical techniques.
Optimization Programming
• Build a tree-based reinforcement learning optimization algorithm applying ensemble dispatching rules and Monte Carlo Tree Search (MCTS) to solve scheduling problems with huge size under short time constraints /* Patent ID : TWI633504 */
• Develop a heuristic algorithm method(Lagrangian relaxation method) to solve scheduling problem in a large scale for searching a good solution in an effective way.
• Develop a integrated system contains efficient meta-heuristics algorithm such as GA, PSO with Chaos-based initialization, ACO and AFSA(Artificial Fish-Swarm Algorithm) to solve classic benchmark including TSP, assignment problem and bin packing problem.
• Experienced in linear programming language such as OOP with Lingo / Cplex package.
• Build a fuzzy inference system contains 10+ membership function in C#.
• Implement Back Propagation Neural Network in C#.
工作經歷
Industrial Technology Research Institute (ITRI)(工業技術研究院, 工研院), Data Analyst & Optimization Analyst (2nd year), Dec 2017 ~ 現在
Focused on reinforcement learning, statistics method and optimization techniques
• Built model to simulate Photolithography & Patterning System and optimize its production schedule. Raise 6.9% PoH(pieces per hour) in 70% cases, 3.75% on average. Total computation time required is less than 5 min. The expected revenue earned is over 50 million (DRAM Devices Industry)
• Developed batching scheduling algorithm and setup a flexible 3-D data structure to storage highly varying scheduling data in small-volume, large-variety production system. Increase 11% order fill rate and reduce 20% computing time (Printed Circuit Board (PCB) Industry)
• Designed dispatching rules to solve mass production scheduling problem with huge size(30000+ jobs and 100+ machines) in 10 minutes. Implement divide and conquer algorithm to saved 80%+ computation time and meet 99% utilization (TFT-LCD Panels Industry)
Industrial Technology Research Institute (ITRI)(工業技術研究院, 工研院), Data Analyst & Optimization Analyst (1st year), Dec 2016 ~ Dec 2017
Intelligent Analytic Tech. Div - Data Analytic Tech. Dept
• Built a tree-based reinforcement learning optimization algorithm applying ensemble dispatching rules and Monte Carlo Tree Search (MCTS) to solve scheduling problems with huge size under short time constraints /* Patent ID : TWI633504 */
• Developed Intelligent Scheduling Technology to solve complicated combination problem and ensured projects were delivered on or ahead of schedule
- Set up the Tree-based Scheduling Algorithm to optimize the schedule problem under many constraints and achieve the required objective(min makespan/WIP/...)
- Built related module in scheduling problems such as batching process, mask transportation, preserving maintenance, out sourcing, reticle sharing, unexpected crash, machine setup and yield issue
• Developed an algorithm to analyze workload of manufacturing system by statistical theory and unsupervised clustering method
LMPMARKET PTE. LTD., Singapore, Partner and Optimization Analyst, Dec 2018 ~ 現在
• Building the programming solver to generate best supply strategy by considering elasticity of capacity between electricity spot market and power generator with long term contractual commitments. Work with Dr. Yen-Shong Chiao, Singapore
• Maintaining programming model to ensure that current solver meets customer needs and constraints
LMPMARKET PTE. LTD., Singapore, Optimization Analyst and Algorithm Programmer, May 2017 ~ Dec 2018
• Power Network Planning and Optimization
- Built and modified the Linear Programming Model to represent a Electric Power Network System
- Solved the problem and determine optimal electric power supply strategy based on known demand and capacity in Java(with Lingo Package)
• Searched for potential strategy to improve transporting strategy by sensitivity analysis and constraints relaxation
- (Seller) Find best power transmission strategy to maximize revenue(at lowest transportation loss)
- (Buyer) Find best transaction strategy to minimize cost(result from price differences of many power generators between different areas)
Industrial Technology Research Institute (ITRI)(工業技術研究院, 工研院) Research Intern - Machine Learning Project, Mar 2015 ~ Dec 2015
• Built a unsupervised clustering model, including hierarchical algorithm(HA) and k-means clustering, to analysis complex time series of indicator, for example, PM10 and PM2.5 concentrations at Taiwan based on data from Taiwan Air Quality Monitoring Network
• Visualized the air quality data by statistical techniques and plot results in R language
• Compared the common machine learning algorithms, including support vector machine, neural network, decision tree, radon forest and so on in various data set in R language in order to realize the characteristic of each algorithm, and organized into technical documents
• Built the simulation model about traffic system for the demonstration of application in data analytic in Java
Cloud Farm, Product Manager, Jun 2012 ~ Jul 2014
Project planning, Web Database Development and Marketing
• Design the MVC(Model–view–controller) architecture of system, and implement the database design and web programming
• Arranged harvesting schedule by considering the planting time, demand and due date of order. Responsible for daily logistics management and shipping
• In charge of sale and communicate with customers, acknowledging of orders and hold the customer complaints
• Lead a team of 8 people and successfully develop e-commerce and business model to expanse distribution channel of local agriculture, increasing 15% of retail revenue
• Analyze the planting process, transforming to manufacturing structure to build food traceability by ERP(Enterprise Resource Planning)
• Target and connect to potential customers who are likely to bulk order and help farmer pricing products, eventually winning the 5 cases of companies order with 200+ carton of agricultural products
Publications
Conference Papers
- Che-Ming Kuo, Heuristic Algorithm for Scheduling of Make-to-Order Plant Factory with Considering Crops Size Variation during Cultivation, Chinese Institute of Industrial Engineers Annual Conference(CIIE2015).
- Kwei-Long Huang, Chao-Lung Yang, Che-Ming Kuo*(corresponding author) and Hao-Chen Weng, A Plant Factory Scheduling Research with Multi-Period Harvest, The 17th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS 2016).
- A Scheduling Research in Plant Factory with Considering Multi-Period Harvest, 2016
- Tsung-Jung Hsieh, Sen-Chia Chang, Yao-Chung Hsu, Che-Ming Kuo, I-Hsuan Chung, Tree Search-Based Scheduling Method and An Apparatus Using the Same (TW I633504B)
學歷
National Taiwan University, 科學碩士（MS）, Industrial Engineering, 2015 ~ 2016
Master Thesis : A Scheduling Research in Plant Factory with Considering Multi-Period Harvest
This study focus on the crop-scheduling problem for a plant factory and consider the special property of crops which can be harvested multiple times. This scheduling problem is formulated as a mixed integer programming (MIP) problem.
The objective function is defined as to find the maximum revenue for the plant factory under the consider of different practical condition including types of crops, cultivation room number, cultivation room space, heterogeneous harvesting amount among different environment of cultivation room and multiple harvesting period.
This study develops a heuristic algorithm method(Lagrangian relaxation method) to solve scheduling problem in a large scale for searching a good solution(gap is less than 20%) in an effective way(reduce 90%+ computing time).
National Taiwan University of Science and Technology, 科學碩士（MS）, Industrial Management, 2014 ~ 2015
Attended, earning 20+ credits in manufacturing, artificial intelligence and algorithm field, and transfer to Nation Taiwan University to got an MS in Industrial Engineering.
National Yunlin University of Science and Technology, 工學學士（BEng）, Industrial Engineering and Management, 2010 ~ 2014
Graduating in the honor of the first lead.