Novel Genetic Bees Algorithm applied to single machine scheduling problem

Michael S. Packianather; Baris Yuce; Ernesto Mastrocinque; Fabio Fruggiero; Duc Truong Pham; Alfredo Lambiase

doi:10.1109/WAC.2014.6936194

Novel Genetic Bees Algorithm applied to single machine scheduling problem

Michael S. Packianather, Baris Yuce, Ernesto Mastrocinque, Fabio Fruggiero, Duc Truong Pham, Alfredo Lambiase

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

18 Citations (Scopus)

Abstract

The proposed novel Genetic Bees Algorithm (GBA) is an enhancement to the swarm-based Bees Algorithm (BA). It is called the Genetic Bees Algorithm because it has genetic operators. The structure of the GBA compared to the basic BA has two extra components namely, a Reinforced Global Search and a Jumping Function. The main advantage of adding the genetic operators to BA is that it will help the algorithm to avoid getting stuck in local optima. In this study the scheduling problem of a single machine was considered. When the basic BA was applied to solve this problem its performance was affected by its weakness in conducting global search to explore the search space. However, in most cases the proposed GBA overcame this issue due to the two new components which have been introduced.

Original language	English
Title of host publication	World Automation Congress (WAC), 2014
Publisher	IEEE
Pages	906-911
Number of pages	6
ISBN (Print)	978-1-889335-49-0
DOIs	https://doi.org/10.1109/WAC.2014.6936194
Publication status	Published - 27 Oct 2014
Event	World Automation Congress - Waikoloa Hilton Village, Kona, Big Island of Hawaii, United States Duration: 3 Aug 2014 → 7 Aug 2014 https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=32651

Conference

Conference	World Automation Congress
Abbreviated title	WAC
Country/Territory	United States
City	Kona, Big Island of Hawaii
Period	3/08/14 → 7/08/14
Internet address	https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=32651

Keywords

barium
genetics
Single machine scheduling
Educational institutions
Optimization
sociology
statistics
single machine scheduling
genetic algorithms
search problems
jumping function
genetic bees algorithm
GBA
single machine scheduling problem
swarm-based bees algorithm
genetic operators
reinforced global search component
Swarm Based Optimisation Technique (SBOT)
Bees Algorithm (BA)
Genetic Bees Algorithm (GBA)

Access to Document

10.1109/WAC.2014.6936194

Ernesto Mastrocinque
- School of Mechanical Engineering - Assistant Professor (Academic)
Person: Teaching and Research

Cite this

@inproceedings{f2d64a8d12a24a099badba97c7aa4ace,

title = "Novel Genetic Bees Algorithm applied to single machine scheduling problem",

abstract = "The proposed novel Genetic Bees Algorithm (GBA) is an enhancement to the swarm-based Bees Algorithm (BA). It is called the Genetic Bees Algorithm because it has genetic operators. The structure of the GBA compared to the basic BA has two extra components namely, a Reinforced Global Search and a Jumping Function. The main advantage of adding the genetic operators to BA is that it will help the algorithm to avoid getting stuck in local optima. In this study the scheduling problem of a single machine was considered. When the basic BA was applied to solve this problem its performance was affected by its weakness in conducting global search to explore the search space. However, in most cases the proposed GBA overcame this issue due to the two new components which have been introduced.",

keywords = "barium, genetics, Single machine scheduling, Educational institutions, Optimization, sociology, statistics, single machine scheduling, genetic algorithms, search problems, jumping function, genetic bees algorithm, GBA, single machine scheduling problem, swarm-based bees algorithm, genetic operators, reinforced global search component, Swarm Based Optimisation Technique (SBOT), Bees Algorithm (BA), Genetic Bees Algorithm (GBA)",

author = "Packianather, {Michael S.} and Baris Yuce and Ernesto Mastrocinque and Fabio Fruggiero and Pham, {Duc Truong} and Alfredo Lambiase",

year = "2014",

month = oct,

day = "27",

doi = "10.1109/WAC.2014.6936194",

language = "English",

isbn = "978-1-889335-49-0",

pages = "906--911",

booktitle = "World Automation Congress (WAC), 2014",

publisher = "IEEE",

address = "United States",

note = "World Automation Congress, WAC ; Conference date: 03-08-2014 Through 07-08-2014",

url = "https://www.ieee.org/conferences_events/conferences/conferencedetails/index.html?Conf_ID=32651",

}

TY - GEN

T1 - Novel Genetic Bees Algorithm applied to single machine scheduling problem

AU - Packianather, Michael S.

AU - Yuce, Baris

AU - Mastrocinque, Ernesto

AU - Fruggiero, Fabio

AU - Pham, Duc Truong

AU - Lambiase, Alfredo

PY - 2014/10/27

Y1 - 2014/10/27

N2 - The proposed novel Genetic Bees Algorithm (GBA) is an enhancement to the swarm-based Bees Algorithm (BA). It is called the Genetic Bees Algorithm because it has genetic operators. The structure of the GBA compared to the basic BA has two extra components namely, a Reinforced Global Search and a Jumping Function. The main advantage of adding the genetic operators to BA is that it will help the algorithm to avoid getting stuck in local optima. In this study the scheduling problem of a single machine was considered. When the basic BA was applied to solve this problem its performance was affected by its weakness in conducting global search to explore the search space. However, in most cases the proposed GBA overcame this issue due to the two new components which have been introduced.

AB - The proposed novel Genetic Bees Algorithm (GBA) is an enhancement to the swarm-based Bees Algorithm (BA). It is called the Genetic Bees Algorithm because it has genetic operators. The structure of the GBA compared to the basic BA has two extra components namely, a Reinforced Global Search and a Jumping Function. The main advantage of adding the genetic operators to BA is that it will help the algorithm to avoid getting stuck in local optima. In this study the scheduling problem of a single machine was considered. When the basic BA was applied to solve this problem its performance was affected by its weakness in conducting global search to explore the search space. However, in most cases the proposed GBA overcame this issue due to the two new components which have been introduced.

KW - barium

KW - genetics

KW - Single machine scheduling

KW - Educational institutions

KW - Optimization

KW - sociology

KW - statistics

KW - single machine scheduling

KW - genetic algorithms

KW - search problems

KW - jumping function

KW - genetic bees algorithm

KW - GBA

KW - single machine scheduling problem

KW - swarm-based bees algorithm

KW - genetic operators

KW - reinforced global search component

KW - Swarm Based Optimisation Technique (SBOT)

KW - Bees Algorithm (BA)

KW - Genetic Bees Algorithm (GBA)

U2 - 10.1109/WAC.2014.6936194

DO - 10.1109/WAC.2014.6936194

M3 - Conference proceeding

SN - 978-1-889335-49-0

SP - 906

EP - 911

BT - World Automation Congress (WAC), 2014

PB - IEEE

T2 - World Automation Congress

Y2 - 3 August 2014 through 7 August 2014

ER -

Novel Genetic Bees Algorithm applied to single machine scheduling problem

Abstract

Conference

Keywords

Access to Document

Fingerprint

Profiles

Ernesto Mastrocinque

Cite this