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To realize autonomous shipping, autonomous berthing and unberthing are some of the technical challenges. In the past, numerous research have been done on the optimization of trajectory planning of berthing problems. However, these studies…

Optimization and Control · Mathematics 2022-01-14 Yoshiki Miyauchi , Ryohei Sawada , Youhei Akimoto , Naoya Umeda , Atsuo Maki

We demonstrate how a genetic algorithm solves the problem of minimizing the resources used for network coding, subject to a throughput constraint, in a multicast scenario. A genetic algorithm avoids the computational complexity that makes…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Minkyu Kim , Varun Aggarwal , Una-May O'Reilly , Muriel Medard , Wonsik Kim

Evolutionary algorithms have been frequently applied to constrained continuous optimisation problems. We carry out feature based comparisons of different types of evolutionary algorithms such as evolution strategies, differential evolution…

Artificial Intelligence · Computer Science 2015-09-24 Shayan Poursoltan , Frank Neumann

The digital transformation of automation places new demands on data acquisition and processing in industrial processes. Logical relationships between acquired data and cyclic process sequences must be correctly interpreted and evaluated. To…

Neural and Evolutionary Computing · Computer Science 2023-04-13 Marlon Löppenberg , Andreas Schwung

Evolutionary algorithms are well suited for solving the knapsack problem. Some empirical studies claim that evolutionary algorithms can produce good solutions to the 0-1 knapsack problem. Nonetheless, few rigorous investigations address the…

Neural and Evolutionary Computing · Computer Science 2014-10-07 Jun He , Boris Mitavskiy , Yuren Zhou

The performance of different mutation operators is usually evaluated in conjunc-tion with specific parameter settings of genetic algorithms and target problems. Most studies focus on the classical genetic algorithm with different parameters…

Neural and Evolutionary Computing · Computer Science 2016-06-03 Chun Liu , Andreas Kroll

Evolutionary algorithms have been applied to a wide range of stochastic problems. Motivated by real-world problems where constraint violations have disruptive effects, this paper considers the chance-constrained knapsack problem (CCKP)…

Neural and Evolutionary Computing · Computer Science 2021-08-02 Yue Xie , Oscar Harper , Hirad Assimi , Aneta Neumann , Frank Neumann

The optimization of dynamic problems is both widespread and difficult. When conducting dynamic optimization, a balance between reinitialization and computational expense has to be found. There are multiple approaches to this. In parallel…

Neural and Evolutionary Computing · Computer Science 2014-01-21 Ronald Hochreiter , Christoph Waldhauser

The PDPTW is an optimization vehicles routing problem which must meet requests for transport between suppliers and customers satisfying precedence, capacity and time constraints. We present, in this paper, a genetic algorithm for…

Neural and Evolutionary Computing · Computer Science 2010-10-06 Imen Harbaoui Dridi , Ryan Kammarti , Pierre Borne , Mekki Ksouri

Few activities are as crucial in urban environments as waste management. Mismanagement of waste can cause significant economic, social, and environmental damage. However, waste management is often a complex system to manage and therefore…

Optimization and Control · Mathematics 2025-05-22 Begoña González , Diego Rossit , Mariano Frutos , Máximo Méndez

In container terminal yards, the Container Rehandling Problem (CRP) involves rearranging containers between stacks under specific operational rules, and it is a pivotal optimization challenge in intelligent container scheduling systems.…

Artificial Intelligence · Computer Science 2025-04-22 Ruoqi Wang , Jiawei Li

The design space of networked embedded systems is very large, posing challenges to the optimisation of such platforms when it comes to support applications with real-time guarantees. Recent research has shown that a number of inter-related…

Performance · Computer Science 2020-07-21 Leandro Soares Indrusiak , Robert I. Davis , Piotr Dziurzanski

The advantages of evolutionary algorithms with respect to traditional methods have been greatly discussed in the literature. While particle swarm optimizers share such advantages, they outperform evolutionary algorithms in that they require…

Neural and Evolutionary Computing · Computer Science 2021-01-28 Johann Sienz , Mauro S. Innocente

Two-dimensional bin packing problems are highly relevant combinatorial optimization problems. They find a large number of applications, for example, in the context of transportation or warehousing, and for the cutting of different materials…

Artificial Intelligence · Computer Science 2012-09-06 Christian Blum , Verena Schmid , Lukas Baumgartner

The productivity and efficiency of port operations strongly depend on how fast a ship can be unloaded and loaded again. With this in mind, ship-to-shore cranes perform the critical task of transporting containers into and onto a ship and…

Systems and Control · Electrical Eng. & Systems 2022-11-21 Filipe Marques Barbosa , Johan Löfberg

The "0-1 knapsack problem" stands as a classical combinatorial optimization conundrum, necessitating the selection of a subset of items from a given set. Each item possesses inherent values and weights, and the primary objective is to…

Neural and Evolutionary Computing · Computer Science 2024-02-20 Mohammad Saleh Vahdatpour

We describe an implementation of a genetic algorithm on partially commutative groups and apply it to the double coset search problem on a subclass of groups. This transforms a combinatorial group theory problem to a problem of combinatorial…

Group Theory · Mathematics 2007-05-23 Matthew Craven

Optimization of ship routing depends on several parameters, like ship and cargo characteristics, environmental factors, topography, international navigation rules, crew comfort etc. The complex nature of the problem leads to…

Mathematical Physics · Physics 2009-05-04 O. T. Kosmas , D. S. Vlachos

During our earlier research, it was recognised that in order to be successful with an indirect genetic algorithm approach using a decoder, the decoder has to strike a balance between being an optimiser in its own right and finding feasible…

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

Heuristic algorithms have shown a good ability to solve a variety of optimization problems. Stockpile blending problem as an important component of the mine scheduling problem is an optimization problem with continuous search space…

Neural and Evolutionary Computing · Computer Science 2021-02-11 Yue Xie , Aneta Neumann , Frank Neumann