Scatter search and path relinking
New ideas in optimization
Tabu Search
A Template for Scatter Search and Path Relinking
AE '97 Selected Papers from the Third European Conference on Artificial Evolution
Sequential and Parallel Path-Relinking Algorithms for the Quadratic Assignment Problem
IEEE Intelligent Systems
Pattern Recognition Letters - Special issue: Evolutionary computer vision and image understanding
New advances and applications for marrying simulation and optimization
WSC '04 Proceedings of the 36th conference on Winter simulation
Advances in analytics: integrating dynamic data mining with simulation optimization
IBM Journal of Research and Development - Business optimization
Comparing Hybrid Versions of SS and DE to Solve a Realistic FAP Problem
HAIS '08 Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems
A memetic algorithm for global optimization in chemical process synthesis
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
A scatter search algorithm for solving vehicle routing problem with loading cost
Expert Systems with Applications: An International Journal
Metaheuristic approaches for optimal broadcasting design in metropolitan MANETs
EUROCAST'07 Proceedings of the 11th international conference on Computer aided systems theory
Unsupervised image segmentation with adaptive archive-based evolutionary multiobjective clustering
PReMI'11 Proceedings of the 4th international conference on Pattern recognition and machine intelligence
An advanced scatter search design for skull-face overlay in craniofacial superimposition
Expert Systems with Applications: An International Journal
Seeking global edges for traveling salesman problem in multi-start search
Journal of Global Optimization
Parameter Estimation Using Metaheuristics in Systems Biology: A Comprehensive Review
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Computers and Operations Research
Optimal broadcasting in metropolitan MANETs using multiobjective scatter search
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
New ideas in applying scatter search to multiobjective optimization
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Staffing optimization in complex service delivery systems
Proceedings of the 7th International Conference on Network and Services Management
A scatter search algorithm for the automatic clustering problem
ICDM'06 Proceedings of the 6th Industrial Conference on Data Mining conference on Advances in Data Mining: applications in Medicine, Web Mining, Marketing, Image and Signal Mining
Path-relinking intensification methods for stochastic local search algorithms
Journal of Heuristics
Investigation on evolutionary computation techniques of a nonlinear system
Modelling and Simulation in Engineering
Combining metaheuristic algorithms to solve a scheduling problem
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part II
libCudaOptimize: an open source library of GPU-based metaheuristics
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Pattern Recognition Letters
Engineering Applications of Artificial Intelligence
On the performance of Scatter Search for post-enrolment course timetabling problems
Journal of Combinatorial Optimization
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The evolutionary approach called scatter search originated from strategies for creating composite decision rules and surrogate constraints. Recent studies demonstrate the practical advantages of this approach for solving a diverse array of optimisation problems from both classical and real--world settings. Scatter search contrasts with other evolutionary procedures, such as genetic algorithms, by providing unifying principles for joining solutions based on generalised path constructions in Euclidean space and by utilising strategic designs where other approaches resort to randomisation. Additional advantages are provided by intensification and diversification mechanisms that exploit adaptive memory, drawing on foundations that link scatter search to tabu search. The main goal of this chapter is to demonstrate the development of a scatter search procedure by demonstrating how it may be applied to a class of non-linear optimisation problems on bounded variables. We conclude the chapter by highlighting key ideas and research issues that offer the promise of yielding future advances.