Special Purpose Computer Architectures for High Speed Optimisation
David Abramson, A de Silva, Marcus Randall, Adam J. Postula · 1995
This paper discussed two computationally intensive optimisation algorithms for 0-1 integer programs, namely simulated annealing and branch and bound. It then describes an application specific computing platform designed to accelerate their performance. The paper justifies the general approach and gives details of the algorithms. 1. Introduction Optimisation is found in many fields, and takes many different forms. Linear programming was first used by Dantzig in 1948 for solving optimisation problems involving linear cost functions and linear constraints. The traditional method for solving such problems has been the Simplex algorithm [1], however, Interior Point methods [2] are now attracting much attention for large problems. Integer programming is used extensively for scheduling activities. Exact algorithms such as branch-and-bound, and heuristic methods such as genetic algorithms and simulated annealing have been used with success. However, large optimisation problems can take a long ...