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 program...
The paper presents an analysis of the use of optimization algorithms in parallel solutions and distr...
Since its introduction as a generic heuristic for discrete optimisation in 1983, simulated annealing...
0–1 problems are often difficult to solve. Although special purpose algorithms (exact as well as heu...
This paper discussed two computationally intensive optimisation algorithms for 0-1 integer programs,...
This paper explores the use of simulated annealing (SA) for solving arbitrary combinatorial optimisa...
The nominal peak speeds of both serial and parallel computers is raising rapidly. At the same time h...
[[abstract]]Complex optimisation problems with many degrees of freedom are often characterised by th...
This Memorandum is a draft version of a review paper which will be submitted to the Bulletin of the ...
The topic for this dissertation is the optimisation of computer programs, as they are being compiled...
Simulated annealing has proven to be a good technique for solving hard combinatorial optimization p...
The goal of the research out of which this monograph grew, was to make annealing as much as possible...
The sequential Branch and Bound Algorithm is the most established method for solving Mixed Integer a...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
Abstract. I consider the problem of the domain-specific optimization of programs. I review different...
AbstractSequential versions of combinatorial optimisation algorithms which are based on random searc...
The paper presents an analysis of the use of optimization algorithms in parallel solutions and distr...
Since its introduction as a generic heuristic for discrete optimisation in 1983, simulated annealing...
0–1 problems are often difficult to solve. Although special purpose algorithms (exact as well as heu...
This paper discussed two computationally intensive optimisation algorithms for 0-1 integer programs,...
This paper explores the use of simulated annealing (SA) for solving arbitrary combinatorial optimisa...
The nominal peak speeds of both serial and parallel computers is raising rapidly. At the same time h...
[[abstract]]Complex optimisation problems with many degrees of freedom are often characterised by th...
This Memorandum is a draft version of a review paper which will be submitted to the Bulletin of the ...
The topic for this dissertation is the optimisation of computer programs, as they are being compiled...
Simulated annealing has proven to be a good technique for solving hard combinatorial optimization p...
The goal of the research out of which this monograph grew, was to make annealing as much as possible...
The sequential Branch and Bound Algorithm is the most established method for solving Mixed Integer a...
Simulated annealing is a combinatorial optimization method based on randomization techniques. The me...
Abstract. I consider the problem of the domain-specific optimization of programs. I review different...
AbstractSequential versions of combinatorial optimisation algorithms which are based on random searc...
The paper presents an analysis of the use of optimization algorithms in parallel solutions and distr...
Since its introduction as a generic heuristic for discrete optimisation in 1983, simulated annealing...
0–1 problems are often difficult to solve. Although special purpose algorithms (exact as well as heu...