A hybrid metaheuristic for minimizing total tardiness and electricity costs

Ahmad Ebrahimi; Hyun Woo Jeon

A hybrid metaheuristic for minimizing total tardiness and electricity costs

Ahmad Ebrahimi
, Hyun Woo Jeon

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

Abstract

This study presents a new particle swarm optimization (PSO) and simulated annealing (SA) algorithm in order to solve a problem minimizing the total production tardiness and electricity costs by controlling scheduling and layout together in a flexible job shop. The proposed algorithm is modified and enhanced from a hybrid PSO-SA algorithm addressed in literature for unconstrained continuous problems. In particular, a new binary representation is designed for the encoding and decoding of solutions. The performance of the developed PSO-SA is evaluated in terms of fitness value and CPU time and is shown to be better than that of PSO in illustrative examples.

Original language	English
Title of host publication	IISE Annual Conference and Expo 2019
Publisher	Institute of Industrial and Systems Engineers, IISE
ISBN (Electronic)	9781713814092
Publication status	Published - 2019
Event	2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019 - Orlando, United States Duration: 18 May 2019 → 21 May 2019

Publication series

Name	IISE Annual Conference and Expo 2019

Conference

Conference	2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019
Country/Territory	United States
City	Orlando
Period	18/05/19 → 21/05/19

Bibliographical note

Publisher Copyright:
© 2019 IISE Annual Conference and Expo 2019. All rights reserved.

Keywords

Electricity cost
Layout
Particle swarm optimization
Scheduling
Simulated annealing
Tardiness cost

Cite this

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title = "A hybrid metaheuristic for minimizing total tardiness and electricity costs",

abstract = "This study presents a new particle swarm optimization (PSO) and simulated annealing (SA) algorithm in order to solve a problem minimizing the total production tardiness and electricity costs by controlling scheduling and layout together in a flexible job shop. The proposed algorithm is modified and enhanced from a hybrid PSO-SA algorithm addressed in literature for unconstrained continuous problems. In particular, a new binary representation is designed for the encoding and decoding of solutions. The performance of the developed PSO-SA is evaluated in terms of fitness value and CPU time and is shown to be better than that of PSO in illustrative examples.",

keywords = "Electricity cost, Layout, Particle swarm optimization, Scheduling, Simulated annealing, Tardiness cost",

author = "Ahmad Ebrahimi and Jeon, \{Hyun Woo\}",

note = "Publisher Copyright: {\textcopyright} 2019 IISE Annual Conference and Expo 2019. All rights reserved.; 2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019 ; Conference date: 18-05-2019 Through 21-05-2019",

year = "2019",

language = "English",

series = "IISE Annual Conference and Expo 2019",

publisher = "Institute of Industrial and Systems Engineers, IISE",

booktitle = "IISE Annual Conference and Expo 2019",

}

Ebrahimi, A & Jeon, HW 2019, A hybrid metaheuristic for minimizing total tardiness and electricity costs. in IISE Annual Conference and Expo 2019., 967275, IISE Annual Conference and Expo 2019, Institute of Industrial and Systems Engineers, IISE, 2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019, Orlando, United States, 18/05/19.

TY - GEN

T1 - A hybrid metaheuristic for minimizing total tardiness and electricity costs

AU - Ebrahimi, Ahmad

AU - Jeon, Hyun Woo

PY - 2019

Y1 - 2019

N2 - This study presents a new particle swarm optimization (PSO) and simulated annealing (SA) algorithm in order to solve a problem minimizing the total production tardiness and electricity costs by controlling scheduling and layout together in a flexible job shop. The proposed algorithm is modified and enhanced from a hybrid PSO-SA algorithm addressed in literature for unconstrained continuous problems. In particular, a new binary representation is designed for the encoding and decoding of solutions. The performance of the developed PSO-SA is evaluated in terms of fitness value and CPU time and is shown to be better than that of PSO in illustrative examples.

AB - This study presents a new particle swarm optimization (PSO) and simulated annealing (SA) algorithm in order to solve a problem minimizing the total production tardiness and electricity costs by controlling scheduling and layout together in a flexible job shop. The proposed algorithm is modified and enhanced from a hybrid PSO-SA algorithm addressed in literature for unconstrained continuous problems. In particular, a new binary representation is designed for the encoding and decoding of solutions. The performance of the developed PSO-SA is evaluated in terms of fitness value and CPU time and is shown to be better than that of PSO in illustrative examples.

KW - Electricity cost

KW - Layout

KW - Particle swarm optimization

KW - Scheduling

KW - Simulated annealing

KW - Tardiness cost

UR - https://www.scopus.com/pages/publications/85095445834

M3 - Conference contribution

AN - SCOPUS:85095445834

T3 - IISE Annual Conference and Expo 2019

BT - IISE Annual Conference and Expo 2019

PB - Institute of Industrial and Systems Engineers, IISE

T2 - 2019 Institute of Industrial and Systems Engineers Annual Conference and Expo, IISE 2019

Y2 - 18 May 2019 through 21 May 2019

ER -

A hybrid metaheuristic for minimizing total tardiness and electricity costs

Abstract

Publication series

Conference

Bibliographical note

Keywords

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Cite this