Using genetic algorithms for supporting combinatorially complex decisions
Pi‐Sheng Deng · 2002
Combinatorially complex decisions are usually characterized by their huge size of solution space. For such type of decisions, optimal solutions are usually unattainable, and we can only approximate the optimal solutions. Due to their deterministicity, most of the traditional optimization techniques are limited by their power to discover satisfactory solutions for combinatorially complex decisions. In this paper, we designed a GA-based interactive system for the support of a combinatorially complex decision, namely the FMS batch selection problem. A performance analysis was conducted for different parameter settings for our system.