Purpose - The purpose of this paper is to propose a local approximation-based search method to optimize any function. For this purpose, an approximation method is combined with an estimation filter, and a new local search mechanism is constituted
The discrete optimization technique called local search yields impressive results on many important ...
This paper proposes a Parallel Guided Local Search (PGLS) framework for continuous optimization. In ...
Abstract—Engineering optimization often involves one or many computationally intensive softwares tha...
This book covers local search for combinatorial optimization and its extension to mixed-variable opt...
International audienceThis chapter sets up a formal framework for local search and provides a certai...
AbstractA new search method is presented for unconstrained optimization. The method requires the eva...
This paper focuses on a subclass of box-constrained, non-linear optimization problems. We are partic...
Proving that a program is correct can be done by translating it into a first-order formula and tryin...
A large number of algorithms introduced in the literature to find the global minimum of a real func...
The paper deals with combinations of the cutting angle method in global optimization and a local sea...
Local search is an integral part of many meta-heuristic strategies that solve single objective optim...
The genetic algorithms (GAs) can be used as a global optimization tool for continuous and discrete f...
Local search is an integral part of many meta-heuristic strategies that solve single objective optim...
Local search algorithms for combinatorial optimization problems are in general of pseudopolynomial r...
In a recent paper, Dennis et al. (SIAM Journal on Optimization 1, pp. 333-357, 1991) introduced a ne...
The discrete optimization technique called local search yields impressive results on many important ...
This paper proposes a Parallel Guided Local Search (PGLS) framework for continuous optimization. In ...
Abstract—Engineering optimization often involves one or many computationally intensive softwares tha...
This book covers local search for combinatorial optimization and its extension to mixed-variable opt...
International audienceThis chapter sets up a formal framework for local search and provides a certai...
AbstractA new search method is presented for unconstrained optimization. The method requires the eva...
This paper focuses on a subclass of box-constrained, non-linear optimization problems. We are partic...
Proving that a program is correct can be done by translating it into a first-order formula and tryin...
A large number of algorithms introduced in the literature to find the global minimum of a real func...
The paper deals with combinations of the cutting angle method in global optimization and a local sea...
Local search is an integral part of many meta-heuristic strategies that solve single objective optim...
The genetic algorithms (GAs) can be used as a global optimization tool for continuous and discrete f...
Local search is an integral part of many meta-heuristic strategies that solve single objective optim...
Local search algorithms for combinatorial optimization problems are in general of pseudopolynomial r...
In a recent paper, Dennis et al. (SIAM Journal on Optimization 1, pp. 333-357, 1991) introduced a ne...
The discrete optimization technique called local search yields impressive results on many important ...
This paper proposes a Parallel Guided Local Search (PGLS) framework for continuous optimization. In ...
Abstract—Engineering optimization often involves one or many computationally intensive softwares tha...
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