Evolution Programs for Various Discrete Problems

Abstract

As stated in the Introduction, it seems that most researchers modified their implementations of genetic algorithms either by using non-standard chromosome representation and/or by designing problem-specific genetic operators (e.g., [141], [385], [65], [76], etc.) to accommodate the problem to be solved, thus building efficient evolution programs. Such modifications were discussed in detail in the previous two chapters (Chapters 9 and 10) for the transportation problem and the traveling salesman problem, respectively. In this chapter, we have made a somewhat arbitrary selection of a few other evolution programs developed by the author and other researchers, which are based on non-standard chromosome representation and/or problem-specific knowledge operators. We discuss some systems for scheduling problems (section 11.1), the timetable problem (section 11.2), partitioning problems (section 11.3), and the path planning problem in mobile robot environment (section 11.4). The chapter concludes with an additional section 11.5, which provides some brief remarks on a few other, interesting problems.

Said a disappointed visitor, ‘Why has my stay here yielded no fruit?’

‘Could it be because you lacked the courage to shake the tree?’ said the Master benignly.

Anthony de Mello, One Minute Wisdom