Discrete Manufacturing Process Design Optimization: Theory and Application
Abstract
Discrete manufacturing process design optimization (DMPDO) is a problem of significant importance and interest to the Air Force. Moreover, the complexity of parts that must be manufactured for airplane engines and other units makes this problem extremely difficult. This report summarizes the research that has been conducted in developing the generalized hill climbing (GHC) algorithm framework for discrete optimization problems in general, and the DMPDO problems in particular. Convergence conditions for GHC algorithms have been developed. Ordinal hill climbing (OHC) algorithms were introduced to exploit the efficiency of ordinal optimization and the effectiveness of GHC algorithms to obtain a new class of discrete optimization problem algorithms. The relationship between OHC algorithms and genetic algorithms was also studied. Multiple sequence optimization using GHC algorithms were introduced to optimize across sets of DMPDO sequences. Simultaneous GHC algorithms were introduced as a generalization to optimize across a set of related discrete optimization problems. On-going interactions with researchers at the Materials Process Design Branch of the AFRL at WPAFB and at Austral Engineering and Software, Inc. has resulted in these algorithms being transitioned for application into commercial software tools designed to solve various DMPDO problems of interest to the Air Force.
Document Details
- Document Type
- Technical Report
- Publication Date
- May 14, 2001
- Accession Number
- ADA393221
Entities
People
- Richard Nance
- Sheldon H. Jacobson
Organizations
- Virginia Tech