Enhancing business process management with simulation optimization
Proceedings of the 38th conference on Winter simulation
Advances in analytics: integrating dynamic data mining with simulation optimization
IBM Journal of Research and Development - Business optimization
Dynamic filters and randomized drivers for the multi-start global optimization algorithm MSNLP
Optimization Methods & Software - GLOBAL OPTIMIZATION
Adaptive memory programming for constrained global optimization
Computers and Operations Research
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Motivated by the successful use of a pseudo-cut strategy within the setting of constrained nonlinear and nonconvex optimization in Lasdon et al. (2010), we propose a framework for general pseudo-cut strategies in global optimization that provides a broader and more comprehensive range of methods. The fundamental idea is to introduce linear cutting planes that provide temporary, possibly invalid, restrictions on the space of feasible solutions, as proposed in the setting of the tabu search metaheuristic in Glover (1989), in order to guide a solution process toward a global optimum, where the cutting planes can be discarded and replaced by others as the process continues. These strategies can be used separately or in combination, and can also be used to supplement other approaches to nonlinear global optimization. Our strategies also provide mechanisms for generating trial solutions that can be used with or without the temporary enforcement of the pseudo-cuts.