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Members: FreeCIS
IEEE Members: Free
Non-members: FreeLength: 00:51:00
08 Jul 2018
Alice Smith Keynote Talk (CEC) at WCCI 2018
Abstract: This presentation will put forth several straightforward but successful implementations of an often overlooked evolutionary algorithm evolutionary strategies, ES for the design of complex systems. ES was developed more than 50 years ago for optimizing engineering design problems in continuous space and is characterized by its simplicity and computational efficiency. There are few tunable parameters in the basic version and the search relies on the evolution of a population through mutation only, where mutation is a Gaussian which adapts automatically to the search history. Such simplicity is appealing for both algorithm development and implementation and tends to result in a robust search. The engineering design problems showcased in this talk are diverse and most involve two objectives optimized with ES simultaneously to identify a Pareto set of non-dominated designs. The applications are (1) the design of an airfoil for a flying drone considering drag and lift, (2) the design of heterogeneous communications networks considering resiliency and traffic efficiency, (3) the location of semi-obnoxious facilities in municipalities considering transport costs and social costs, and (4) the design of large order picking warehouses considering travel distance.
Abstract: This presentation will put forth several straightforward but successful implementations of an often overlooked evolutionary algorithm evolutionary strategies, ES for the design of complex systems. ES was developed more than 50 years ago for optimizing engineering design problems in continuous space and is characterized by its simplicity and computational efficiency. There are few tunable parameters in the basic version and the search relies on the evolution of a population through mutation only, where mutation is a Gaussian which adapts automatically to the search history. Such simplicity is appealing for both algorithm development and implementation and tends to result in a robust search. The engineering design problems showcased in this talk are diverse and most involve two objectives optimized with ES simultaneously to identify a Pareto set of non-dominated designs. The applications are (1) the design of an airfoil for a flying drone considering drag and lift, (2) the design of heterogeneous communications networks considering resiliency and traffic efficiency, (3) the location of semi-obnoxious facilities in municipalities considering transport costs and social costs, and (4) the design of large order picking warehouses considering travel distance.
