Improving Schedule Quality through Case-Based Reasoning
Kazuo Miyashita · 2002
We describe a framework, implemented in CAB-INS, for iterative schedule revision based on acqui-sition and reuse of user optimization preferences to improve schedule quality. Practical scheduling problems generally require allocation of resources in the presence of a large, diverse and typically conflicting set of constraints and optimization cri-teria. The ill-structuredness of both the solution space and the desired objectives make scheduling problems difficult to formalize. CABINS records situation-dependent tradeoffs about repair actions and schedule quality to guide schedule improve-ment. During iterative repair, cases are exploited for: (1) repair action selection, (2) evaluation intermediate repair results and (3) recovery from revision failures. The contributions of the work lie in experimentally demonstrating in a domain where neither the user nor the program possess causal knowledge of the domain that (a) taking into consideration failure information in the form of failed cases or a repair history of a case im-proves schedule quality, (b) schedule quality im-proves with increasing case size and (c) preserv-ing the case base rather than inducing rules gives better results.