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- » The best paper of Journal Chinese Institute of Industrial Engineering of 2006 (April 24, 2007 Released)
Congratulation!
March 5, 2008
The best paper of Journal Chinese Institute of Industrial Engineering of 2007
"TWater Flow-like Algorithm for Object Grouping Problems " (Volumn 24, No. 6, 2007)
by Feng-Cheng Yang and Yuan-Peng Wang pp.
ABSTRACT
This paper presents a novice heuristic algorithm, Water Flow-like Algorithm (WFA), for solving discrete optimization problems, particularly the bin packing problems. WFA simulates solution agents as water flows traversing the terrain mapped from the objective function. Governed by the gravitation force, water flows from higher attitudes to lower ones. Driven by the fluid momentum, water flows adjust their compositions and directions against the landforms by splitting into and merging from other flows. Water flows are allowed to move upward to higher attitudes once they possess enough momentum to overcome the potential barrier. Mostly, at least one flow can travel to the lowest region of the terrain under the consideration. In the atmosphere, some water of a flow will evaporate and return to the ground by precipitation. Inspired by the water flowing of the nature, WFA is designed as an optimization algorithm performing the water flow splitting, merging, and dropping (precipitation) operations to traverse the solution space. The number of solution agents deployed is dynamically changing. WFA is an evolutionary algorithm involving four water flow operations: splitting and moving, merging, evaporation, and precipitation. The computational flow and the four operations are extensively discussed. In addition to general operations of WFA, specific operations for bin packing problems are presented. A designed problem and a benchmark problem from OR-Lib are used to test WFA and to compare results with other methods, such as GA, POS, and EM. Numerical results show that WFA outperforms others in solving these BPPs.
Keywords:heuristic algorithm, discrete optimization, water flow-like algorithm, flow merging, flow splitting
Professor Yuan-Shin Lee Elected IIE Fellow
May 1, 2007
Professor Yuan-Shin Lee of Industrial and Systems Engineering at North Carolina State University has been elected as a Fellow of the Institute of Industrial Engineers (IIE). This award is the highest classification of membership in IIE and is in recognition of outstanding leaders of the profession that have made significant, nationally and internationally recognized contributions to industrial engineering. The Council of Fellows represents many of the most prominent members of the industrial engineering profession.
Professor Lee also received the Technical Innovation Award from IIE in 2006. He will be formally recognized as a Fellow at the IIE Annual Conference in May 2007.
IIE is the world's largest professional membership society dedicated solely to the support of the industrial engineering profession and individuals involved with improving quality and productivity.
Congratulation!
April 24, 2007
The best paper of Journal Chinese Institute of Industrial Engineering of 2006
"Tool Planning in Multiple Product-Mix under Cycle Time Constraints for Wafer Foundries Using Genetic Algorithm" (Volumn 23, No. 2, 2006)
by Dr. ?Yai Hsiung, Dr. Muh-Cherng Wu, and Dr.? Hsi-Mei Hsu.
ABSTRACT
Tool planning is to determine the number of tools in each workstation for achieving some objectives. This paper formulates and solves a tooling problem in the context of multi-product mix, where the mean cycle time must be under a predefined target. Due to demand variation, a wafer foundry frequently faces the need to manufacture in various product-mix. Previous literature has addressed the issue of multiple product-mix, yet the cycle time constraint has not been considered. Cycle time is a key performance index for wafer foundries and should not be ignored in their tool planning. We propose a genetic algorithm based solution methodology embedded with a queuing analysis to solve the problem. Test examples reveals that the proposed solution greatly outperforms that obtained by a single product mix planning.
Keywords: tool planning, cycle time, multiple product mix, GA (genetic algorithm), wafer foundry