Browsing by Author "Suganthan, Ponnuthurai Nagaratnam"

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Citation - WoS: 13
Citation - Scopus: 15
A General Variable Neighborhood Search Algorithm for the No-Idle Permutation Flowshop Scheduling Problem
(SPRINGER-VERLAG BERLIN, 2013) M. Fatih Tasgetiren; Ozge Buyukdagli; Quan-Ke Pan; Ponnuthurai Nagaratnam Suganthan; Tasgetiren, M. Fatih; Suganthan, Ponnuthurai Nagaratnam; Buyukdagli, Ozge; Pan, Quan-Ke; BK Panigrahi; PN Suganthan; S Das; SS Dash
In this study a general variable neighborhood search (GVNS) is presented to solve no-idle permutation flowshop scheduling problem (NIPFS) where idle times are not allowed on machines. GVNS is a metaheuristic where inner loop operates a variable neighborhood descend (VND) algorithm whereas the outer loop carries out some perturbations on the current solution. We employ a simple insert and swap moves in the outer loop whereas iterated greedy (IG) and iterated local search (ILS) algorithms are employed in the VND as neighborhood structures. The results of the GVNS algorithm are compared to those generated by the variable iterated greedy algorithm with differential evolution (vIG_DE). The performance of the proposed algorithm is tested on the Ruben Ruiz' benchmark suite that is presented in http://soa.iti.es/rruiz. Computational results showed that the GVNS algorithm further improved 85 out of 250 best solutions found so far in the literature.
Citation - WoS: 84
Citation - Scopus: 97
An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time
(Taylor and Francis Ltd., 2015) Kaizhou Gao; Ponnuthurai Nagaratnam Suganthan; Quanke Pan; M. Fatih Tasgetiren; Suganthan, Ponnuthurai Nagaratnam; Tasgetiren, Mehmet Fatih; Gao, Kai Zhou; Pan, Quan Ke
This study addresses flexible job shop scheduling problem (FJSP) with fuzzy processing time. The fuzzy or uncertainty of processing time is one of seven characteristics in remanufacturing. A discrete harmony search (DHS) algorithm is proposed for FJSP with fuzzy processing time. The objective is to minimise maximum fuzzy completion time. A simple and effective heuristic rule is proposed to initialise harmony population. Extensive computational experiments are carried out using five benchmark cases with eight instances from remanufacturing. The proposed heuristic rule is evaluated using five benchmark cases. The proposed DHS algorithm is compared to six metaheuristics. The results and comparisons show the effectiveness and efficiency of DHS for solving FJSP with fuzzy processing time. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 132
Citation - Scopus: 151
Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion
(Elsevier B.V., 2016) Kaizhou Gao; Ponnuthurai Nagaratnam Suganthan; Quanke Pan; M. Fatih Tasgetiren; Ali Sadollah; Suganthan, Ponnuthurai Nagaratnam; Tasgetiren, Mehmet Fatih; Sadollah, Ali; Gao, Kai Zhou; Pan, Quan Ke
This study addresses flexible job shop scheduling problem (FJSP) with two constraints namely fuzzy processing time and new job insertion. The uncertainty of processing time and new job insertion are two scheduling related characteristics in remanufacturing. Fuzzy processing time is used to describe the uncertainty in processing time. Rescheduling operator is executed when new job(s) is (are) inserted into the schedule currently being executed. A two-stage artificial bee colony (TABC) algorithm with several improvements is proposed to solve FJSP with fuzzy processing time and new job insertion constraints. Also several new solution generation methods and improvement strategies are proposed and compared with each other. The objective is to minimize maximum fuzzy completion time. Eight instances from remanufacturing are solved using the proposed TABC algorithm. The proposed improvement strategies are compared and discussed in detail. Two proposed ABC algorithms with the best performances are compared against seven existing algorithms over by five benchmark cases. The optimization results and comparisons show the competitiveness of the proposed TABC algorithm for solving FJSP. © 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 64
Citation - Scopus: 76
Effective ensembles of heuristics for scheduling flexible job shop problem with new job insertion
(Elsevier Ltd, 2015) Kaizhou Gao; Ponnuthurai Nagaratnam Suganthan; M. Fatih Tasgetiren; Quanke Pan; Qiangqiang Sun; Suganthan, Ponnuthurai Nagaratnam; Tasgetiren, Mehmet Fatih; Sun, Qiang Qiang; Gao, Kai Zhou; Pan, Quan Ke
This study investigates the flexible job shop scheduling problem (FJSP) with new job insertion. FJSP with new job insertion includes two phases: initializing schedules and rescheduling after each new job insertion. Initializing schedules is the standard FJSP problem while rescheduling is an FJSP with different job start time and different machine start time. The time to do rescheduling is the same as the time of new job insertion. Four ensembles of heuristics are proposed for scheduling FJSP with new job insertion. The objectives are to minimize maximum completion time (makespan) to minimize the average of earliness and tardiness (E/T) to minimize maximum machine workload (Mworkload) and total machine workload (Tworkload). Extensive computational experiments are carried out on eight real instances from remanufacturing enterprise. The results and comparisons show the effectiveness of the proposed heuristics for solving FJSP with new job insertion. © 2015 Elsevier B.V. All rights reserved.
Citation - WoS: 8
Citation - Scopus: 14
Multi-Objective Optimization For Shading Devices in Buildings By Using Evolutionary Algorithms
(IEEE, 2016) Ayca Kirimtat; Basak Kundakci Koyunbaba; Ioannis Chatzikonstantinou; Sevil Sariyildiz; Ponnuthurai Nagaratnam Suganthan; Sariyildiz, Sevil; Chatzikonstantinou, Ioannis; Suganthan, Ponnuthurai Nagaratnam; Koyunbaba, Basak Kundakci; Kirimtat, Ayca
The reduction of energy consumption is a major challenge around the world. Architectural aspects have a significant place to minimize energy consumption to the maximum level. The use of large glazed facades causes overheating problems in certain climatic regions. Shading elements must be considered at an early stage in the design process to overcome this problem. An application of the method is presented focusing on the horizontal louvers integrated to a building in Izmir Turkey. The contributions of the paper can be summarized as follows. We show that most architectural design problems are basically real-parameter multi-objective constrained optimization problems. So any type of evolutionary and swarm optimization methods can be used in this field. A multi-objective self-adaptive differential evolution algorithm (jDEMO) inspired from the DEMO algorithm from the literature with some modifications is developed and compared to the well-known fast and nondominated sorting genetic algorithm so called NSGA-II in order to solve this complex problem and identify alternative design solutions to decision makers. Through the experimental results we show that the proposed algorithm generated slightly better results when comparing to the NSGA-II algorithm.
Citation - Scopus: 2
Solving Lot-streaming Flow Shop Scheduling Problems Using a Discrete Harmony Search Algorithm
(IEEE, 2010) Quan-Ke Pan; Mehmet Fatih Tasgetiren; Ponnuthurai Nagaratnam Suganthan; Yun-Chia Liang; Tasgetiren, Mehmet Fatih; Suganthan, Ponnuthurai Nagaratnam; Liang, Yun-Chia; Pan, Quan-Ke
The harmony search (HS) algorithm is one of the recent evolutionary computation techniques to solve optimization problems. To make it applicable for lot-streaming flow shop problems a discrete variant of the HS algorithm (DHS) with job permutations representation is proposed. In the proposed DHS algorithm a new improvisation scheme is designed to generate feasible job sequences. A local search algorithm based on the insert neighborhood structure is fused to stress the further enhancement capability of the algorithm proposed whereas a restart scheme is employed to avoid the stagnation of the evolution. Extensive computational simulations and comparisons are provided which demonstrate the effectiveness of the proposed DHS against the best performing algorithms from the literature.