Effective heuristic methods for finding non-optimal solutions of interest in constrained optimization models

• المؤلفون الرئيسيون: KIMBROUGH, Steven O., KUO, Ann, LAU, Hoong Chuin
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2010
• الموضوعات: sensitivity analysis; deliberation support; constrained optimization; post-solution analysis; candle-lighting analysis; Artificial Intelligence and Robotics; Numerical Analysis and Scientific Computing; Operations Research, Systems Engineering and Industrial Engineering
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/355; https://ink.library.smu.edu.sg/context/sis_research/article/1354/viewcontent/effective_heuristic_methods_1.pdf

This paper introduces the SoI problem, that of finding nonoptimal solutions of interest for constrained optimization models. SoI problems subsume finding FoIs (feasible solutions of interest), and IoIs (infeasible solutions of interest). In all cases, the interest addressed is post-solution analysis in one form or another. Post-solution analysis of a constrained optimization model occurs after the model has been solved and a good or optimal solution for it has been found. At this point, sensitivity analysis and other questions of import for decision making (discussed in the paper) come into play and for this purpose the SoIs can be of considerable value. The paper presents examples that demonstrate this and reports on a systematic approach, using evolutionary computation, for obtaining both FoIs and IoIs.