ISE 789: Syllabus
Professor S.-C. Fang (email@example.com)
450 | 111 Lampe Drive
- Office Hours
Tu, Th 2:30 – 3:30 PM (or by appointment)
OR501 Introduction to Operations Research or equivalent
This course is to introduce the basic concepts of soft computing methodology and to provide hand-on experience for problem solving. We shall spend about 4 weeks on fuzzy sets and systems, 3 weeks on neural networks, 5 weeks on genetic algorithms, simulated annealing, tabu search and other methods.
- Fuzzy Sets and Systems
- Neural Networks
- Genetic Algorithms
- Simulated Annealing
- Tabu Search
- Other Methods
- Homeworks – 20%
- Projects – 30%
- Midterm – 20%
- Final – 30%
- A – 88 and above
- B – 75 to 87
- C – 60 to 74
- Fail – under 60
- About 7 assignments.
- Solution sets will be posted by TA.
- Rule 1: No late homework without TA’s approval
- Rule 2: Convince TA for any grade changes.
- Rule 3: No make-up exam without my pre-approval or “emergency notes” from hospital.
- Midterm: in-class with one 4×6 index card.
- Final: Comprehensive take home.
H.-J. Zimmermann, “Fuzzy Set Theory and Its Applications” (QA248.Z55 1996), Kluwer Academic Publishers, 1996, 3rd Edition.
Murray Smith, “Neural Networks for Statistical Modeling” (QA76.87.S62 1993), International Thomson Computer Press, 1993.
J.-S.R. Jang, C.-T. Sun and E. Mizutani: “Neuro-Fuzzy and Soft Computing” (QA76.9.S63J36 1997), Prentice Hall, 1997.
Mitsuo Gen and Runwei Cheng, “Genetic Algorithms & Engineering Optimization” (T56.24.G46 2000), Wiley-Interscience, 2000.