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49 results on '"Pongcharoen, Pupong"'

2. Automated Computational Intelligence Based Course Timetabling Tool

Author

Kuntasup, Marisa, Pongcharoen, Pupong, Thepphakorn, Thatchai, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Cheung, Simon K. S., editor, Wang, Fu Lee, editor, Paoprasert, Naraphorn, editor, Charnsethikul, Peerayuth, editor, Li, Kam Cheong, editor, and Phusavat, Kongkiti, editor

Published
2024
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7. Static and Dynamic Parameter Settings of Accelerated Particle Swarm Optimisation for Solving Course Scheduling Problem

Author

Thepphakorn, Thatchai, Sooncharoen, Saisumpan, Pongcharoen, Pupong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, and Luo, Yuhua, editor

Published
2020
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9. Academic Operating Costs Optimisation Using Hybrid MCPSO Based Course Timetabling Tool

Author

Thepphakorn, Thatchai, Sooncharoen, Saisumpan, Pongcharoen, Pupong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cheung, Simon K. S., editor, Li, Richard, editor, Phusavat, Kongkiti, editor, Paoprasert, Naraphorn, editor, and Kwok, Lam‑For, editor

Published
2020
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10. A Deep Learning Tool Using Teaching Learning-Based Optimization for Supporting Smart Learning Environment

Author

Sooncharoen, Saisumpan, Thepphakorn, Thatchai, Pongcharoen, Pupong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Cheung, Simon K. S., editor, Li, Richard, editor, Phusavat, Kongkiti, editor, Paoprasert, Naraphorn, editor, and Kwok, Lam‑For, editor

Published
2020
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11. Variants and Parameters Investigations of Particle Swarm Optimisation for Solving Course Timetabling Problems

Author

Thepphakorn, Thatchai, Pongcharoen, Pupong, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Tan, Ying, editor, Shi, Yuhui, editor, and Niu, Ben, editor

Published
2019
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18. A New Multiple Objective Cuckoo Search for University Course Timetabling Problem

Author

Thepphakorn, Thatchai, Pongcharoen, Pupong, Vitayasak, Srisatja, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sombattheera, Chattrakul, editor, Stolzenburg, Frieder, editor, Lin, Fangzhen, editor, and Nayak, Abhaya, editor

Published
2016
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19. Application of Genetic Algorithm for Quantifying the Affect of Breakdown Maintenance on Machine Layout

Author

Vitayasak, Srisatja, Pongcharoen, Pupong, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sombattheera, Chattrakul, editor, Stolzenburg, Frieder, editor, Lin, Fangzhen, editor, and Nayak, Abhaya, editor

Published
2016
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22. Genetic Algorithm Based Robust Layout Design By Considering Various Demand Variations

Author

Vitayasak, Srisatja, Pongcharoen, Pupong, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Tan, Ying, editor, Shi, Yuhui, editor, Buarque, Fernando, editor, Gelbukh, Alexander, editor, Das, Swagatam, editor, and Engelbrecht, Andries, editor

Published
2015
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23. Bat Algorithm, Genetic Algorithm and Shuffled Frog Leaping Algorithm for Designing Machine Layout

Author

Dapa, Kittipong, Loreungthup, Pornpat, Vitayasak, Srisatja, Pongcharoen, Pupong, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Ramanna, Sheela, editor, Lingras, Pawan, editor, Sombattheera, Chattrakul, editor, and Krishna, Aneesh, editor

Published
2013
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25. Improving Artificial Immune System Performance: Inductive Bias and Alternative Mutations

Author

Pongcharoen, Pupong, Chainate, Warattapop, Pongcharoen, Sutatip, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Bentley, Peter J., editor, Lee, Doheon, editor, and Jung, Sungwon, editor

Published
2008
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28. A Hybrid Discrete Bat Algorithm with Krill Herd-based advanced planning and scheduling tool for the capital goods industry.

Author

Chansombat, Sirikarn, Musikapun, Ponnapa, Pongcharoen, Pupong, and Hicks, Christian

Subjects
ADVANCED planning & scheduling, METAHEURISTIC algorithms, INDUSTRIAL equipment, ALGORITHMS, PLANT products, BEES algorithm
Abstract

Capital goods companies produce high value products such as power plant or ships, which have deep and complex product structures, with components having long process routings. Contracts usually include substantial penalties for late delivery. The high value of items can lead to substantial holding costs. Efficient schedules minimise earliness and tardiness costs and need to satisfy assembly and operation precedence constraints as well as finite capacity. This paper presents the first advanced planning and scheduling (APS) tool for the capital goods industry that uses a Discrete Bat Algorithm (DBA), modified DBA (MDBA) and hybrid DBA with Krill Herd algorithm (HDBK) to optimise schedules. The tool was validated using four data-sets obtained from a collaborating capital goods company. A sequential experimental strategy was adopted. The first experiment identified appropriate parameter settings for the DBA. The second experiment evaluated and compared the performance of the proposed HDBK algorithm with an Artificial Bee Colony, Krill Herd (KH), Modified KH, DBA and MDBA metaheuristics. The experimental results revealed that the HDBK performed best in terms of the minimum penalty cost for all problem sizes and achieved up to a 47.837% reduction in mean total penalty costs of extra-large problem size. [ABSTRACT FROM AUTHOR]

Published
2019
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29. A mixed-integer linear programming model for integrated production and preventive maintenance scheduling in the capital goods industry.

Author

Chansombat, Sirikarn, Pongcharoen, Pupong, and Hicks, Christian

Subjects
MIXED integer linear programming, LINEAR programming, PRODUCTION scheduling, MANUFACTURING processes, PRODUCTION control, INDUSTRIAL engineering
Abstract

The scheduling literature is extensive, but much of this work is theoretical and does not capture the complexity of real world systems. Capital goods companies produce products with deep and complex product structures, each of which requires the coordination of jobbing, batch, flow and assembly processes. Many components require numerous operations on multiple machines. Integrated scheduling problems simultaneously consider two or more simultaneous decisions. Previous production scheduling research in the capital goods industry has neglected maintenance scheduling and used metaheuristics with stochastic search that cannot guarantee an optimal solution. This paper presents a novel mixed integer linear programming model for simultaneously solving the integrated production and preventive maintenance scheduling problem in the capital goods industry, which was tested using data from a collaborating company. The objective was to minimise total costs including: tardiness and earliness penalty costs; component and assembly holding costs; preventive maintenance costs; and set-up, production, transfer and production idle time costs. Thus, the objective function and problem formulation were more extensive than previous research. The tool was successfully tested using data obtained from a collaborating company. It was found that the company's total cost could be reduced by up to 63.5%. [ABSTRACT FROM AUTHOR]

Published
2019
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38. Applying different control approaches for resources with high and low utilisation: a case study of the production of complex products with stochastic processing times

Author

Hicks, Christian and Pongcharoen, Pupong

Subjects
Stochastic processes -- Analysis, Production management -- Technology application, Technology application, Business, international, High technology industry, Science and technology
Abstract

Byline: Christian Hicks, Pupong Pongcharoen Research on dispatching rules has mainly focused upon deterministic job shop situations or small assembly environments and has ignored operational factors. Recent work has examined the relative performance of dispatching rules in companies that produce several families of complex products with stochastic processing times. Previous work has used common control policies for all resources. In practice, it is common for there to be a wide variation in the utilisation of machines. The Optimised Production Technology (OPT) philosophy suggests that particular attention should be paid to bottleneck resources. This paper investigates the effect of applying different manufacturing control approaches for resources with high and low utilisation. The work uses data obtained from an Engineer-To-Order (ETO) capital goods company that produces complex products in low volume. Processing times are assumed to be normally distributed. A range of scenarios are considered in which an increasing proportion of resources are considered to be 'bottlenecks'. The results show that the mean tardiness of products decreases significantly when the highly utilised machines are carefully controlled. However, there is only marginal benefit in carefully controlling the other machines.

Published
2009

41. A Multiple Criteria Genetic Algorithm Scheduling Tool for Production Scheduling in the Capital Goods Industry

Author

Xie, Wenbin, Hicks, Chris, Pongcharoen, Pupong, Xie, Wenbin, Hicks, Chris, and Pongcharoen, Pupong

Abstract

Production planners usually aim to satisfy multiple objectives. This paper describes the development of a genetic algorithm tool that finds optimum trade-offs among delivery performance, resource utilisation, and workin-progress inventory. The tool was specifically developed to meet the requirements of capital goods companies that manufacture products with deep and complex product structures with components that have long and complicated routings. The model takes into account operation and assembly precedence relationships and finite capacity constraints. The tool was tested using various production problems that were obtained from a collaborating company. A series of experiments showed the tool provides a set of non-dominated solutions that enable the planner to choose an optimum trade-off according to their preferences. Previous research had optimised a single objective function. This is the first scheduling tool of its type that has simultaneously optimised delivery performance, resource utilisation and work-in-progress inventory. The quality of the schedules produced was significantly better than the approaches used by the collaborating company.

Published
2014

49. ScienceAsia

Author

Pongcharoen, Pupong, primary, Chainate, Watthanapol, additional, and Samranpun, Chaowanee, additional

Published
2007
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