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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

Flexible job shop scheduling has been noticed as an effective manufacturing system to cope with rapid development in today's competitive environment. Flexible job shop scheduling problem (FJSSP) is known as a NP-hard problem in the field of…

Optimization and Control · Mathematics 2012-07-11 Sayedmohammadreza Vaghefinezhad , Kuan Yew Wong

Problems affecting the transport of people or goods are plentiful in industry and commerce and they also appear to be at the origin of much more complex problems. In recent years, the logistics and transport sector keeps growing supported…

Artificial Intelligence · Computer Science 2020-09-23 Alessandro Bertagnon

This study presents a hybrid metaheuristic for the resource-constrained project scheduling problem (RCPSP), which integrates a genetic algorithm (GA) and a neighborhood search strategy (NS). The RCPSP consists of a set of activities that…

Optimization and Control · Mathematics 2025-09-15 Evgenii Goncharov

This paper proposes Genetic Algorithm with Border Trades (GAB), a novel modification of the standard genetic algorithm that enhances exploration by incorporating new chromosome patterns in the breeding process. This approach significantly…

Machine Learning · Computer Science 2025-06-27 Qingchuan Lyu

We continue the study of Genetic Algorithms (GA) on combinatorial optimization problems where the candidate solutions need to satisfy a balancedness constraint. It has been observed that the reduction of the search space size granted by…

Neural and Evolutionary Computing · Computer Science 2022-06-23 Luca Manzoni , Luca Mariot , Eva Tuba

A substantial disadvantage of traditional learning is that all students follow the same learning sequence, but not all of them have the same background of knowledge, the same preferences, the same learning goals, and the same needs.…

Artificial Intelligence · Computer Science 2021-04-26 Lumbardh Elshani , Krenare Pireva Nuçi

Evolutionary algorithms (EAs), such as the genetic algorithm (GA), offer an elegant way to handle combinatorial optimization problems (COPs). However, limited by expertise and resources, most users do not have enough capability to implement…

Neural and Evolutionary Computing · Computer Science 2022-05-30 Bowen Zhao , Wei-Neng Chen , Feng-Feng Wei , Ximeng Liu , Qingqi Pei , Jun Zhang

In real life, it is always an urge to reach our goal in minimum effort i.e., it should have a minimum constrained path. The path may be shortest route in practical life, either physical or electronic medium. The scenario is to represents…

Neural and Evolutionary Computing · Computer Science 2014-01-14 Sounak Sadhukhan , Samar Sen Sarma

Search-based Software Engineering has been utilized for a number of software engineering activities. One area where Search-Based Software Engineering has seen much application is test data generation. Evolutionary testing designates the use…

Software Engineering · Computer Science 2011-03-02 P. Maragathavalli

Projects consist of interconnected dimensions such as objective, time, resource and environment. Use of these dimensions in a controlled way and their effective scheduling brings the project success. Project scheduling process includes…

Artificial Intelligence · Computer Science 2019-02-05 Muhammed Hanefi Calp , Muhammet Ali Akcayol

Various neural network models have been proposed to tackle combinatorial optimization problems such as the travelling salesman problem (TSP). Existing learning-based TSP methods adopt a simple setting that the training and testing data are…

Machine Learning · Computer Science 2022-04-08 Zeyang Zhang , Ziwei Zhang , Xin Wang , Wenwu Zhu

The user-level brokers in grids consider individual application QoS requirements and minimize their cost without considering demands from other users. This results in contention for resources and sub-optimal schedules. Meta-scheduling in…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-03-10 Saurabh Garg , Pramod Konugurthi , Rajkumar Buyya

The travelling salesperson problem (TSP) is a classic resource allocation problem used to find an optimal order of doing a set of tasks while minimizing (or maximizing) an associated objective function. It is widely used in robotics for…

Robotics · Computer Science 2022-07-19 Ishaan Mehta , Sharareh Taghipour , Sajad Saeedi

The Traveling Thief Problem (TTP) is a multi-component optimization problem that captures the interplay between routing and packing decisions by combining the classical Traveling Salesperson Problem (TSP) and the Knapsack Problem (KP). The…

Data Structures and Algorithms · Computer Science 2026-04-22 Jan Eube , Kelin Luo , Aneta Neumann , Frank Neumann , Heiko Röglin

Genetic Algorithms (GAs) are powerful metaheuristic techniques mostly used in many real-world applications. The sequential execution of GAs requires considerable computational power both in time and resources. Nevertheless, GAs are…

Neural and Evolutionary Computing · Computer Science 2013-12-17 Filomena Ferrucci , M-Tahar Kechadi , Pasquale Salza , Federica Sarro

The traveling salesman problem (TSP) is one of the most challenging NP-hard problems. It has widely applications in various disciplines such as physics, biology, computer science and so forth. The best known approximation algorithm for…

Data Structures and Algorithms · Computer Science 2016-12-13 Wenhong Tian , Chaojie Huang , Xinyang Wang , Qin Xiong

The job sequencing and tool switching problem (SSP) has been extensively studied in the field of operations research, due to its practical relevance and methodological interest. Given a machine that can load a limited amount of tools…

Neural and Evolutionary Computing · Computer Science 2019-10-23 Jordana Mecler , Anand Subramanian , Thibaut Vidal

In this paper, a high-level comparison of both SOAP (Simple Object Access Protocol) and REST (Representational State Transfer) is made. These are the two main approaches for interfacing to the web with web services. Both approaches are…

Neural and Evolutionary Computing · Computer Science 2011-05-26 P. A. Castillo , J. L. Bernier , M. G. Arenas , J. J. Merelo , P. Garcia-Sanchez

Most neural solvers for the Traveling Salesperson Problem (TSP) are trained to output a single solution, even though practitioners rarely stop there: at test time, they routinely spend extra compute on sampling or post-hoc search. This…

Machine Learning · Computer Science 2026-05-04 Andoni Irazusta Garmendia