Packing with biased random-key genetic algorithms topic of EBC Speaker Series

The upcoming Engineering, Business, and Computing (EBC) Division Speaker Series Presentation will focus on 2D/3D bin packing with biased random-key genetic algorithms. Mauricio G. C. Resende, Lead Member of Technical Staff at AT&T Labs Research in Middletown, New Jersey, will give the presentation on Wednesday, October 1, 2014, in room 244 of the Gaige Technology and Business Innovation Building. This presentation is free and open to the public, and light refreshments will be served.

According to the abstract, a biased random-key genetic algorithm (BRKGA) is a general search metaheuristic for finding optimal or near-optimal solutions to hard combinatorial optimization problem. It is derived from the random-key genetic algorithm of Bean (1994), differing in the way solutions are combined to produce offspring. Such features simplify and standardize the metaheuristic with a set of self-contained tasks from which only chromosome decoding is problem-dependent. Decoding constructs a solution to the underlying optimization problem, from which the objective function value or fitness can be computed. BRKGAs allow for natural hybridizations of heuristics. An open-source C++ application programming interface (API) for BRKGA is available (Toso & Resende, 2014) allowing for fast implementation of BRKGAs.

In this talk, Resende introduces BRKGAs and describes heuristics based on BRKGAs for orthogonal 2- and 3-dimensional packing, as well as for 2- and 3-dimensional bin packing. These heuristics have produced new best-known solutions for a number of benchmark instances from the packing literature.

Resende is a research scientist at AT&T Shannon Laboratory, AT&T Labs Research in Middletown, New Jersey. His undergraduate studies were in electrical engineering at the Catholic University of Rio de Janeiro, Brazil, and he earned a M.Sc. in operations research at the Georgia Institute of Technology. He has been at AT&T Bell Labs and AT&T Labs Research since 1987, when he earned his Ph.D. in operations research at the University of California, Berkeley.

His research has focused on optimization, including interior point algorithms for linear programming, network optimization, and nonlinear programming, as well as heuristics for discrete optimization problems arising in telecommunications, scheduling, location, assignment, and graph theory. Most of his work with heuristics has concentrated on GRASP (greedy randomized adaptive search procedures), a metaheuristic that he and Thomas A. Feo developed in the late 1980s, and more recently on biased random-key genetic algorithms.

He has published more than 150 papers and is co-editor of five books, including the Handbook of Optimization in Telecommunications and the Handbook of Applied Optimization. He is on the editorial boards of many journals, including Networks, Journal of Heuristics, Journal of Global Optimization, and Computational Optimization and Applications. Besides working in the telecommunications industry, he has worked in the electrical power and semiconductor manufacturing industries, where he developed several decision support systems for optimization problems. In December 2014, he will join as a research scientist.

For more information, contact either of the co-chairs for the EBC Division Speaker Series: Dr. Jui-Chi Huang, Assistant Professor of Economics, [email protected] or Dr. Ada Leung, Assistant Professor of Marketing [email protected].