Commercial Scatter Search Implementation
In this chapter we discuss the development of commercial optimization software based on the scatter search methodology. The OptQuest Callable Library (OCL), which we began developing in the fall of 1998 in collaboration with Fred Glover and James P. Kelly, is the optimization engine of the OptQuest system1. The main goal of OptQuest is to optimize complex systems, which we consider to be those that cannot be easily formulated as mathematical models and solved with classical optimization tools. Many real world optimization problems in business, engineering and science are too complex to be given tractable mathematical formulations. Multiple nonlinearities, combinatorial relationships and uncertainties often render challenging practical problems inaccessible to modeling except by resorting to more comprehensive tools (like computer simulation). Classical optimization methods encounter grave difficulties when dealing with the optimization problems that arise in the context of complex systems. In some instances, recourse has been made to itemizing a series of scenarios in the hope that at least one will give an acceptable solution. Due to the limitations of this approach, a long-standing research goal has been to create a way to guide a series of complex evaluations to produce high quality solutions, in the absence of tractable mathematical structures. (In the context of optimizing simulations, a “complex evaluation” refers to the execution of a simulation model given a set of values for key input parameters.)
KeywordsObjective Function Infeasible Solution Nonlinear Constraint Scatter Search Error Code
Unable to display preview. Download preview PDF.