A projection method for the uncapacitated facility location problem
Mathematical Programming: Series A and B
Parallel simulated annealing techniques
CNLS '89 Proceedings of the ninth annual international conference of the Center for Nonlinear Studies on Self-organizing, Collective, and Cooperative Phenomena in Natural and Artificial Computing Networks on Emergent computation
Stepwise-overlapped parallel annealing and its application to floorplan designs
Computer-Aided Design
Job shop scheduling by simulated annealing
Operations Research
A parallel simulated annealing algorithm
Parallel Computing
Future Generation Computer Systems - Special issue: high performance computing and networking (HPCN)
Parallel simulated annealing for shape detection
Computer Vision and Image Understanding
The annealing evolution algorithm as function optimizer
Parallel Computing
Parallel simulated annealing by mixing of states
Journal of Computational Physics
An effective hybrid optimization strategy for job-shop scheduling problems
Computers and Operations Research
Vector quantization based on genetic simulated annealing
Signal Processing
Fast parallel heuristics for the job shop scheduling problem
Computers and Operations Research
On the use of genetic algorithms to solve location problems
Computers and Operations Research - Location analysis
A methodological approach to parallel simulated annealing on an SMP System
Journal of Parallel and Distributed Computing
A scalable and robust framework for distributed applications
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Parallelism and evolutionary algorithms
IEEE Transactions on Evolutionary Computation
A discrete particle swarm optimization algorithm for uncapacitated facility location problem
Journal of Artificial Evolution and Applications - Particle Swarms: The Second Decade
Metaheuristic Agent Teams for Job Shop Scheduling Problems
HoloMAS '07 Proceedings of the 3rd international conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing
Improved orthogonal array based simulated annealing for design optimization
Expert Systems with Applications: An International Journal
A Comparative Investigation on Heuristic Optimization of WCDMA Radio Networks
Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
Robotics and Computer-Integrated Manufacturing
Simulated annealing algorithm with adaptive neighborhood
Applied Soft Computing
Optimizing reserve capacity of urban road networks in a discrete Network Design Problem
Advances in Engineering Software
Solving job shop scheduling problem using a hybrid parallel micro genetic algorithm
Applied Soft Computing
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
A continuous particle swarm optimization algorithm for uncapacitated facility location problem
ANTS'06 Proceedings of the 5th international conference on Ant Colony Optimization and Swarm Intelligence
A variable neighbourhood search algorithm for job shop scheduling problems
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
A hybrid intelligent model for order allocation planning in make-to-order manufacturing
Applied Soft Computing
Inventory based two-objective job shop scheduling model and its hybrid genetic algorithm
Applied Soft Computing
A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA
Applied Soft Computing
Evolutionary path generation for reduction of thermal variations in thermal spray coating
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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In this paper, the Evolutionary Simulated Annealing (ESA) algorithm, its distributed implementation (dESA) and its application to two combinatorial problems are presented. ESA consists of a population, a simulated annealing operator, instead of the more usual reproduction operators used in evolutionary algorithms, and a selection operator. The implementation is based on a multi island (agent) system running on the Distributed Resource Machine (DRM), which is a novel, scalable, distributed virtual machine based on Java technology. As WAN/LAN systems are the most common multi-machine systems, dESA implementation is based on them rather than any other parallel machine. The problems tackled are well-known combinatorial optimisation problems, namely, the classical job-shop scheduling problem and the uncapacitated facility location problem. They are difficult benchmarks, widely used to measure the efficiency of metaheuristics with respect to both the quality of the solutions and the central processing unit (CPU) time spent. Both applications show that dESA solves problems finding either the optimum or a very near optimum solution within a reasonable time outperforming the recent reported approaches for each one allowing the faster solution of existing problems and the solution of larger problems.