Marc Sevaux – författare

Embedded systems are everywhere in contemporary life and are supposed to make our lives more comfortable. In industry, embedded systems are used to manage and control complex systems (e.g. nuclear power plants, telecommunications and flight control) and they are also taking an important place in our daily activities (e.g. smartphones, security alarms and traffic lights). In the design of embedded systems, memory allocation and data assignment are among the main challenges that electronic designers have to face. In fact, they impact heavily on the main cost metrics (power consumption, performance and area) in electronic devices. Thus designers of embedded systems have to pay careful attention in order to minimize memory requirements, thus improving memory throughput and limiting the power consumption by the system’s memory. Electronic designers attempt to minimize memory requirements with the aim of lowering the overall system costs. A state of the art of optimization techniques for memory management and data assignment is presented in this book.

Embedded systems are everywhere in contemporary life and are supposed to make our lives more comfortable. In industry, embedded systems are used to manage and control complex systems (e.g. nuclear power plants, telecommunications and flight control) and they are also taking an important place in our daily activities (e.g. smartphones, security alarms and traffic lights). In the design of embedded systems, memory allocation and data assignment are among the main challenges that electronic designers have to face. In fact, they impact heavily on the main cost metrics (power consumption, performance and area) in electronic devices. Thus designers of embedded systems have to pay careful attention in order to minimize memory requirements, thus improving memory throughput and limiting the power consumption by the system’s memory. Electronic designers attempt to minimize memory requirements with the aim of lowering the overall system costs. A state of the art of optimization techniques for memory management and data assignment is presented in this book.

This volume constitutes the refereed proceedings of Metaheuristics on 15th International Conference, MIC 2024, held in Lorient, France, during June 4–7, 2024.

The 36 full papers presented together with 34 short papers were carefully reviewed and selected from 127 submissions. The conference focuses on artificial intelligence, combinatorial optimization, computer science, graph theory, evolutionary algorithms, genetic algorithms, simulated annealing, optimization, optimization problems.

This volume constitutes the refereed proceedings of Metaheuristics on 15th International Conference, MIC 2024, held in Lorient, France, during June 4–7, 2024.

The 36 full papers presented together with 34 short papers were carefully reviewed and selected from 127 submissions. The conference focuses on artificial intelligence, combinatorial optimization, computer science, graph theory, evolutionary algorithms, genetic algorithms, simulated annealing, optimization, optimization problems.

One of the keystones in practical metaheuristic problem-solving is the fact that tuning the optimization technique to the problem under consideration is crucial for achieving top performance. This tuning/customization is usually in the hands of the algorithm designer, and despite some methodological attempts, it largely remains a scientific art. Transferring a part of this customization effort to the algorithm itself -endowing it with smart mechanisms to self-adapt to the problem- has been a long pursued goal in the field of metaheuristics.

These mechanisms can involve different aspects of the algorithm, such as for example, self-adjusting the parameters, self-adapting the functioning of internal components, evolving search strategies, etc.

Recently, the idea of hyperheuristics, i.e., using a metaheuristic layer for adapting the search by selectively using different low-level heuristics, has also been gaining popularity. This volume presents recent advances in the area of adaptativeness in metaheuristic optimization, including up-to-date reviews of hyperheuristics and self-adaptation in evolutionary algorithms, as well as cutting edge works on adaptive, self-adaptive and multilevel metaheuristics, with application to both combinatorial and continuous optimization.

Most developed economics show the tendency of an increasing importance of modern services such as tourism, logistical services, finance, and others. In many cases, complex optimization problems can be found in this context, and the successful operation of modern services often depends on the ability to solve the obtained optimization models. Metaheuristics on the other hand present an interesting problem-resolution paradigm that has attracted considerable interest in past years. The book combines a set of selected and peer-reviewed articles, presenting novel results of metaheuristics for modern services. In particular, applications in the area of transportation and logistics are considered, while other areas include production and financial services. Novel methodological approaches as well as improved results are obtained, resulting in a considerable contribution to the state-of-the-art of research in metaheuristics.