Reactive Search integrates sub-symbolic machine learning techniques into search
heuristics for solving complex optimization problems. By automatically adjusting the working …

Matheuristics are heuristic algorithms based on mathematical tools such as the ones
provided by mathematical programming, that are structurally general enough to be applied …

Autonomous search is a particular case of adaptive systems that improve their solving
performance by modifying and adjusting themselves to the problem at hand, either by self …

Abstract We propose the Multi-Constructor CMSA, a Construct, Merge, Solve and Adapt
(CMSA) algorithm that employs multiple heuristic procedures, respectively solution …

During the last few years we have witnessed impressive developments in the area of
stochastic local search techniques for intelligent optimization and Reactive Search …

The transportation industry expanded rapidly in a highly competitive environment. Logistics
companies with insufficient volume of transport capacities are forced to make a selection of …

The unit commitment problem (UCP) for thermal units consists of finding an optimal
electricity production plan for a given time horizon. In this paper we propose hybrid …

Abstract Reactive Search Optimization advocates the integration of sub-symbolic machine
learning techniques into search heuristics for solving complex optimization problems. The …

This book is about learning for problem solving.[...] Human problem solving is strongly
connected to learning. Learning takes places when the problem at hand is not well known at …

Mobile phone operators need to plan and schedule field force personnel for maintenance
and repair tasks on mobile phone base stations across the country on a daily basis. In this …