This chapter deals with the application of evolutionary approaches and other metaheuristic techniques for generating tree decompositions. Tree decomposition is a concept introduced by Robertson and Seymour [34] and it is used to characterize the difficulty of constraint satisfaction and NP-hard problems that can be represented as a graph. Although in general no polynomial algorithms have been f...

We consider the multi-vehicle one-to-one pickup and delivery problem with split loads, a NP-hard problem linked with a variety of applications for bulk product transportation, bike-sharing systems and inventory re-balancing. This problem is notoriously difficult due to the interaction of two challenging vehicle routing attributes, “pickups and deliveries” and “split deliveries”. This possibly l...

This paper presents two metaheuristic algorithms, namely taboo search and simulated annealing, applied to the control of a flow rack automated storage retrieval system (AS/RS). These metaheuristic algorithms are developed to control the retrieval machine of the AS/RS in order to minimize the retrieval cycle time. Results of these metaheuristic algorithms are compared to classical heuristics and...

This paper introduces a cooperative parallel metaheuristic for solving the capacitated vehicle routing problem. The proposed metaheuristic consists of multiple parallel tabu search threads that cooperate by asynchronously exchanging best found solutions through a common solution pool. The solutions sent to the pool are clustered according to their similarities. The search history information id...

In studies of genetic algorithms, evolutionary computing, and ant colony mechanisms, it is recognized that the higher-order forms of collective intelligence play an important role in metaheuristic computing and computational intelligence. Collective intelligence is an integration of collective behaviors of individuals in social groups or collective functions of components in computational intel...

A new approach for the problem of optimal task scheduling in flexible manufacturing systems is proposed in this work, as a combination of metaheuristic optimization techniques with the supervisory control theory of discrete-event systems. A specific encoding, the word-shuffling encoding, which avoids the generation of a large number of infeasible sequences, is employed. A metaheuristic method b...

A challenging part of Software Testing entails the generation of test cases, whose costs can be reduced by means of the use of techniques for automating this task. On the other hand, the nature of Software Engineering problems is ideal for the application of metaheuristic techniques. In this paper we present an approach based on the metaheuristic technique Scatter Search for the automatic test ...

The use of techniques for automating the generation of test scripts is important as it can reduce the time and cost of the process. The recent method for automatic generation of tests using metaheuristic techniques i.e. Genetic Algorithms and Simulated Annealing. There is a great deal of research into the use of Genetic Algorithms to obtain a specific coverage in software testing but none is us...

Due to the fact that the error surface of adaptive infinite impulse response (IIR) systems is generally nonlinear and multimodal, the conventional derivative based techniques fail when used in adaptive identification of such systems. In this case, global optimization techniques are required in order to avoid the local minima. Harmony search (HS), a musical inspired metaheuristic, is a recently ...