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This paper presented a genetic algorithm (GA) to solve the container storage problem in the port. This problem is studied with different container types such as regular, open side, open top, tank, empty and refrigerated containers. The…

Neural and Evolutionary Computing · Computer Science 2013-03-06 I. Ayachi , R. Kammarti , M. Ksouri , P. Borne , : , LAGIS , Ecole Centrale de Lille , : , LACS , Ecole Nationale des Ingenieurs de Tunis

In this work we use multiple scattering in conjunction with a genetic algorithm to reliably determine the optimized photonic-crystal-based structure able to perform a specific optical task. The genetic algorithm operates on a population of…

Materials Science · Physics 2009-11-10 L. Sanchis , A. Hakansson , D. Lopez-Zenon , J. Bravo-Abad , J. Sanchez-Dehesa

Evolvable hardware (EHW) is a set of techniques that are based on the idea of combining reconfiguration hardware systems with evolutionary algorithms. In other word, EHW has two sections; the reconfigurable hardware and evolutionary…

Neural and Evolutionary Computing · Computer Science 2011-10-06 Parisa Soleimani , Reza Sabbaghi-Nadooshan , Sattar Mirzakuchaki , Mahdi Bagheri

Path Planning methods for autonomously controlling swarms of unmanned aerial vehicles (UAVs) are gaining momentum due to their operational advantages. An increasing number of scenarios now require autonomous control of multiple UAVs, as…

Robotics · Computer Science 2024-12-05 Alejandro Puente-Castro , Enrique Fernandez-Blanco , Daniel Rivero

The paper represents an algorithm for planning safe and optimal routes for transport facilities with unrestricted movement direction that travel within areas with obstacles. Paper explains the algorithm using a ship as an example of such a…

Neural and Evolutionary Computing · Computer Science 2019-05-15 Ivan Yanchin , Oleg Petrov

Quantum computing is a new way of data processing based on the concept of quantum mechanics. Quantum circuit design is a process of converting a quantum gate to a series of basic gates and is divided into two general categories based on the…

Emerging Technologies · Computer Science 2017-03-16 Moein Sarvaghad-Moghaddam

Industrial robots are designed as general-purpose hardware with limited ability to adapt to changing task requirements or environments. Modular robots, on the other hand, offer flexibility and can be easily customized to suit diverse needs.…

Robotics · Computer Science 2024-03-05 Jonathan Külz , Matthias Althoff

The design of quantum circuits is often still done manually, for instance by following certain patterns or rule of thumb. While this approach may work well for some problems, it can be a tedious task and present quite the challenge in other…

Quantum Physics · Physics 2023-05-11 Leo Sünkel , Darya Martyniuk , Denny Mattern , Johannes Jung , Adrian Paschke

The Quadratic Assignment Problem (QAP) is one of the models used for the multi-row layout problem with facilities of equal area. There are a set of n facilities and a set of n locations. For each pair of locations, a distance is specified…

Neural and Evolutionary Computing · Computer Science 2014-05-21 Hosein Azarbonyad , Reza Babazadeh

We investigate the use of a Genetic Algorithm (GA) to design a set of photonic crystals (PCs) in one and two dimensions. Our flexible design methodology allows us to optimize PC structures which are optimized for specific objectives. In…

Optics · Physics 2009-11-13 Joel Goh , Ilya Fushman , Dirk Englund , Jelena Vuckovic

This thesis investigates the use of problem-specific knowledge to enhance a genetic algorithm approach to multiple-choice optimisation problems.It shows that such information can significantly enhance performance, but that the choice of…

Neural and Evolutionary Computing · Computer Science 2010-07-05 Uwe Aickelin

The rapid advances in the field of optimization methods in many pure and applied science pose the difficulty of keeping track of the developments as well as selecting an appropriate technique that best suits the problem in-hand. From a…

Neural and Evolutionary Computing · Computer Science 2011-12-30 Loris Serafino

Genetic algorithms constitute a family of black-box optimization algorithms, which take inspiration from the principles of biological evolution. While they provide a general-purpose tool for optimization, their particular instantiations can…

Neural and Evolutionary Computing · Computer Science 2023-04-11 Robert Tjarko Lange , Tom Schaul , Yutian Chen , Chris Lu , Tom Zahavy , Valentin Dalibard , Sebastian Flennerhag

Functions of chemical composition are complex and discrete in nature making it impossible to optimize them with gradient methods. Genetic algorithms, which do not use derivative information, are used to maximize the thermal conductivity of…

Materials Science · Physics 2018-01-30 Alexander Kerr , Kieran Mullen

This paper addresses the optimization of human-robot collaborative work-cells before their physical deployment. Most of the times, such environments are designed based on the experience of the system integrators, often leading to…

Robotics · Computer Science 2025-03-05 Christian Cella , Matteo Bruce Robin , Marco Faroni , Andrea Maria Zanchettin , Paolo Rocco

A Genetic Algorithm (GA) is proposed in which each member of the population can change schemata only with its neighbors according to a rule. The rule methodology and the neighborhood structure employ elements from the Cellular Automata (CA)…

Neural and Evolutionary Computing · Computer Science 2007-11-16 Vasileios Barmpoutis , Gary F. Dargush

The paper presents a method for failure free genetic algorithm optimization of a system controller. Genetic algorithms present a powerful tool that facilitates producing near-optimal system controllers. Applied to such methods of…

Neural and Evolutionary Computing · Computer Science 2007-05-23 E. S. Sazonov , D. Del Gobbo , P. Klinkhachorn , R. L. Klein

This paper explores the use of genetic algorithms for the design of networks, where the demands on the network fluctuate in time. For varying network constraints, we find the best network using the standard genetic algorithm operators such…

Neural and Evolutionary Computing · Computer Science 2009-11-10 Matthew J. Berryman , Andrew Allison , Derek Abbott

The genetic algorithm (GA) is an optimization and search technique based on the principles of genetics and natural selection. A GA allows a population composed of many individuals to evolve under specified selection rules to a state that…

Neural and Evolutionary Computing · Computer Science 2016-08-14 Yılmaz Kaya , Murat Uyar , Ramazan Tek\D{j}n

The functionality of catalysts, enzymes, and supramolecular assemblies emerges not from individual molecules alone, but from the subtle interplay between multiple components arranged in complex systems. Designing such systems is a grand…

Computational Physics · Physics 2026-04-15 Rhyan Barrett , Robin Curth , Julia Westermayr