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Current Practice in Evolutionary Computation Prabhas Chongstitvatana Faculty of Engineering Chulalongkorn University 15 June 2010.

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Presentation on theme: "Current Practice in Evolutionary Computation Prabhas Chongstitvatana Faculty of Engineering Chulalongkorn University 15 June 2010."— Presentation transcript:

1 Current Practice in Evolutionary Computation Prabhas Chongstitvatana Faculty of Engineering Chulalongkorn University 15 June 2010

2 Genetic Algorithms Create population While not terminate – Evaluate – Selection, recombination, mutation

3 Genetic Programming Individual has a tree structure –Variable length –Has semantic attached to a node label

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5 Estimation of Distribution Algorithms Create an initial model While not terminate –Generate population from model –Evaluate –Selection –Learning model from population

6 Lead-free Solder Alloys Lead-based Solder Low cost and abundant supply Forms a reliable metallurgical joint Good manufacturability Excellent history of reliable use Toxicity Lead-free Solder No toxicity Meet Government legislations (WEEE & RoHS) Marketing Advantage (green product) Increased Cost of Non-compliant parts Variation of properties (Bad or Good)

7 Sn-Ag-Cu (SAC) Solder Advantage Sufficient Supply Good Wetting Characteristics Good Fatigue Resistance Good overall joint strength Limitation Moderate High Melting Temp Long Term Reliability Data

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9 Combine with Genetic Programming

10 Experiments Thermal Properties Testing (DSC) - Liquidus Temperature - Solidus Temperature - Solidification Range 10 Solder Compositions Wettability Testing (Wetting Balance; Globule Method) - Wetting Time - Wetting Force

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12 Simultaneous Matrix

13 Partitioning

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16 Coincidence Algorithm

17 Pseudo code for COIN 1.Initialize the generator. 2.Generate the population using the generator. 3.Evaluate the population. 4.Select the candidates. 5.For each joint probability h(xi|xj), update the generator according to the reward and punishment 6.Repeat Step 2. Until the terminate condition is met.

18 Reward and Punishment

19 Complete line assignment for straight assembly line. Complete line assignment for U-shaped assembly line

20 Teamwork

21 Aporntewan, C. and Chongstitvatana, P., "Building block identification by simulateneity matrix for hierarchical problems", Genetic and Evolutionary Computation Conference, Seattle, USA, 26-30 June 2004, Proc. part 1, pp.877-888. Aporntewan, C., Chongstitvatana, P., "Building-block identification by simultaneity matrix". Soft Computing, Vol.11, No.6, 2007, pp.541- 548. Wattanapornprom, W. and Chongstitvatana, P., "Multi-objective Combinatorial Optimisation with Coincidence Algorithm," IEEE Congress on Evolutionary Computation, Norway, May 18-21, 2009. Chedtha Puncreobutr, Gobboon Lohthongkum, Prabhas Chongstitvattana, Boonrat Lohwongwatana,"Modeling of Reflow Temperatures and Wettability in Lead-free Solder Alloys using Hybrid Evolutionary Algorithms," Symp of Pb-Free Solders and Emerging Interconnect and Packaging Technologies (TMS 2010), February 14-18, 2010, Seattle, USA.

22 prabhas@chula.ac.th www.cp.eng.chula.ac.th/faculty/pjw/


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