AbstractSet partitioning problems are among NP-Hard problems due to their complexities. It is difficult to prepare an algorithm that will give a precise solution in these types of problems which are difficult to solve. This study proposes a genetic algorithm based approach among artificial intelligence optimization algorithms in order to find simpler solutions to set partitioning problems. The proposed method was applied to the solution of problem of partitioning the 53 teams in the Turkish Third League into 5 subsets. The distribution of the teams into subsets was undertaken with the aim of minimizing the travel costs and the travel fatigue and preventing the subjective distinctions in the determination of subsets. This study was carried o...
The implementation and evaluation of several algorithms for the solution of the partitioning pro...
Practical pattern classification and knowledge discovery problems require selection of a subset of a...
There is increasing need to solve large-scale complex optimization problems in a wide variety of sci...
AbstractSet partitioning problems are among NP-Hard problems due to their complexities. It is diffic...
This paper describes a parallel genetic algorithm developed for the solution of the set partitioning...
In this study balancing is taken into consideration in the formation of groups according to the tota...
This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Scien...
Crew pairing, which constitute the one phase of airline crew planning is deliberated in this study....
Given a set of individuals, a collection of admissible subsets, and a cost associated to each of the...
The efficient implementation of parallel processing architectures generally requires the solution of...
This paper exposes a research of the NP-hard Maximally Balanced Connected Partition problem (MBCP). ...
The partitioning a set of professional programmers into a set of teams when a programming project sp...
Partitioning graphs into equally large groups of nodes, minimizing the number of edges between diffe...
Genetic Algorithms are evolutionary algorithms used to solve non-deterministic polynomial time probl...
Abstract. In this work we consider large-scale set partitioning problems. Our main purpose is to sho...
The implementation and evaluation of several algorithms for the solution of the partitioning pro...
Practical pattern classification and knowledge discovery problems require selection of a subset of a...
There is increasing need to solve large-scale complex optimization problems in a wide variety of sci...
AbstractSet partitioning problems are among NP-Hard problems due to their complexities. It is diffic...
This paper describes a parallel genetic algorithm developed for the solution of the set partitioning...
In this study balancing is taken into consideration in the formation of groups according to the tota...
This thesis submitted in partial fulfillment of the requirements for the degree of Bachelor of Scien...
Crew pairing, which constitute the one phase of airline crew planning is deliberated in this study....
Given a set of individuals, a collection of admissible subsets, and a cost associated to each of the...
The efficient implementation of parallel processing architectures generally requires the solution of...
This paper exposes a research of the NP-hard Maximally Balanced Connected Partition problem (MBCP). ...
The partitioning a set of professional programmers into a set of teams when a programming project sp...
Partitioning graphs into equally large groups of nodes, minimizing the number of edges between diffe...
Genetic Algorithms are evolutionary algorithms used to solve non-deterministic polynomial time probl...
Abstract. In this work we consider large-scale set partitioning problems. Our main purpose is to sho...
The implementation and evaluation of several algorithms for the solution of the partitioning pro...
Practical pattern classification and knowledge discovery problems require selection of a subset of a...
There is increasing need to solve large-scale complex optimization problems in a wide variety of sci...