A hybrid genetic algorithm–neural network strategy for simulation optimization

The solution of complex system design problems using decomposition-based optimization methods requires determination of appropriate problem partitioning and coordination strategies. Previous optimal partitioning techniques have not addressed the coordination issue explicitly. This article presents a formal approach to simultaneous partitioning and coordination strategy decisions that can provide insights on whether a decomposition-based method will be effective for a given problem. Pareto-optimal solutions are generated to quantify tradeoffs between the sizes of subproblems and coordination problems as measures of the computational costs resulting from different partitioning and coordination strategies. Promising preliminary results with small test problems are presented. The approach is illustrated on an electric water pump design problem.

/pdf/optimal-partitioning-and-coordination-decisions-in-24xoq82swi.pdf

Optimal Partitioning and Coordination Decisions in Decomposition-Based Design Optimization

Optimal Partitioning and Coordination Decisions in Decomposition-Based Design

In this paper, the basic characteristics of particle swarm optimization (PSO) for the global search are discussed at first, and then the PSO for the mixed discrete nonlinear problems (MDNLP) is suggested. The penalty function approach to handle the discrete design variables is employed, in which the discrete design variables are handled as the continuous ones by penalizing at the intervals. As a result, a useful method to determine the penalty parameter of penalty term for the discrete design variables is proposed. Through typical mathematical and structural optimization problems, the validity of the proposed approach for the MDNLP is examined.

Penalty function approach for the mixed discrete nonlinear problems by particle swarm optimization

Many companies have started to investigate Virtual Reality as a tool for evaluating digital mock-ups. One of the key functions needed for interactive evaluation is real-time collision detection. An algorithm for exact collision detection is presented which can handle arbitrary non-convex polyhedra efficiently. The approach attains its speed by a hierarchical adaptive space subdivision scheme, the BoxTree, and an associated divide-andconquer traversal algorithm, which exploits the very special geometry of boxes. The traversal algorithm is generic, so it can be endowed with other semantics operating on polyhedra, e.g., distance computations. The algorithm is fairly simple to implement and it is described in great detail in an “ftp-able” appendix to facilitate easy implementation. Pre-computation of auxiliary data structures is very simple and fast. The efficiency of the approach is shown by timing results and two real-world digital mock-up scenarios.

/pdf/real-time-and-exact-collision-detection-for-interactive-8li1qe1n4d.pdf

Real-time and exact collision detection for interactive virtual prototyping

http://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-pdf/doi/10.1115/DETC1993-0339/6666610/499_1_detc1993-0339.pdf

A Genetic Algorithm for Solving Mixed Discrete Optimization Problems

A New Approach to Intelligent Design

Properties of the Coupled Factors in MDO and Their Application in Collaborative Optimization

http://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-pdf/doi/10.1115/DETC1995-0069/6654635/523_1_detc1995-0069.pdf

A Heuristic Method for Two-Dimensional Layout Problems

http://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-pdf/doi/10.1115/DETC1993-0340/6666606/505_1_detc1993-0340.pdf

An Efficient Genetic Algorithm for Large Scale Built-Up Structural Optimization

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