Optimization of complex systems has evolved in recent years, with current techniques and solutions much more robust, efficient, and accurate than was the case earlier. Leveraging research from some of the top experts in the field, including Dr. Fred Glover and Professor Rafael Marti, Dr. Manuel Laguna explains the use of linear programming and heuristics, their limitations in solving complex optimization problems, and the more recent evolution and growth of metaheuristics. Next, general purpose, “black box” optimizers are outlined in terms of pros and cons in solving real-world problems. Following this general discussion is a detail depiction of OptTek’s black box optimizer, “OptQuest,” including the different types of problems that can be solved, array of variable types and constraints that can be employed, and wide variety of advanced search and predictive techniques utilized. Dr. Laguna concludes his paper with the depiction of several examples demonstrating the use of OptQuest to solve differing optimization problems.
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