This paper addresses the development of general purpose meta-heuristic based combinatorial optimisation algorithms. With this system, a user can specify a problem in a high level algebraic language based on linked list data structures, rather than conventional vector notation. The new formulation is much more concise than the vector form, and lends itself to search heuristics based on local neighbourhood operators . The specification is then compiled into C code, and a unique solver is generated for each particular problem. Currently, search engines for simulated annealing, greedy search and Tabu search have been implemented, and good results have been achieved over a wide range of optimisation problems. We have also implemented a special p...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
AbstractSequential versions of combinatorial optimisation algorithms which are based on random searc...
We introduce a meta-heuristic to combine simulated annealing with local search methods for CO proble...
This paper addresses the development of general purpose meta-heuristic based combinatorial optimisat...
In recent years, there have been many studies in which tailored heuristics and meta-heuristics have ...
In theoretical computer science, combinatorial optimization problems are about finding an optimal it...
There are numerous combinatorial optimization problems, for which computing exact optimal solutions ...
This research presents an attempt to solve a student’s problem in the University to travel in seven ...
Abstract: This research presents an attempt to solve a logistic company’s problem of delivering petr...
International audienceLocal Search metaheuristics are a recognized means of solving hard combinatori...
Combinatorial optimization problems are ubiquitous in real life and hence a wide range of solving pa...
This book covers local search for combinatorial optimization and its extension to mixed-variable opt...
The goal of this research is to develop a systematic, integrated method of designing efficient searc...
We introduce a metaheuristic framework for combinatorial optimization. Our framework is similar to o...
[[abstract]]This paper presents a solution approach for addressing travelling salesman problems by a...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
AbstractSequential versions of combinatorial optimisation algorithms which are based on random searc...
We introduce a meta-heuristic to combine simulated annealing with local search methods for CO proble...
This paper addresses the development of general purpose meta-heuristic based combinatorial optimisat...
In recent years, there have been many studies in which tailored heuristics and meta-heuristics have ...
In theoretical computer science, combinatorial optimization problems are about finding an optimal it...
There are numerous combinatorial optimization problems, for which computing exact optimal solutions ...
This research presents an attempt to solve a student’s problem in the University to travel in seven ...
Abstract: This research presents an attempt to solve a logistic company’s problem of delivering petr...
International audienceLocal Search metaheuristics are a recognized means of solving hard combinatori...
Combinatorial optimization problems are ubiquitous in real life and hence a wide range of solving pa...
This book covers local search for combinatorial optimization and its extension to mixed-variable opt...
The goal of this research is to develop a systematic, integrated method of designing efficient searc...
We introduce a metaheuristic framework for combinatorial optimization. Our framework is similar to o...
[[abstract]]This paper presents a solution approach for addressing travelling salesman problems by a...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
AbstractSequential versions of combinatorial optimisation algorithms which are based on random searc...
We introduce a meta-heuristic to combine simulated annealing with local search methods for CO proble...