Chapter · January 1, 2024
Electrical and Electronic Equipment (EEE) has evolved into a gateway for accessing technological innovations. However, EEE imposes substantial pressure on the environment due to the shortened life cycles. E-waste encompasses discarded EEE and its component ...
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Journal ArticleScientific reports · May 2023
The present study investigates the use of algorithm selection for automatically choosing an algorithm for any given protein-ligand docking task. In drug discovery and design process, conceptualizing protein-ligand binding is a major problem. Targeting this ...
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Chapter · January 1, 2023
The present study applies Algorithm Selection to automatically specify the suitable algorithms for Large-Scale Multi-objective Optimization. Algorithm Selection has known to benefit from the strengths on multiple algorithm rather than relying one. This tra ...
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Conference2023 IEEE Congress on Evolutionary Computation, CEC 2023 · January 1, 2023
The present study utilizes neural network to perform heuristic selection in selection hyper-heuristics. Selection hyper-heuristics are problem-independent solvers, preferably benefited for tackling a wide range of search and optimization problems. Unlike t ...
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ConferenceIEEE International Conference on Automation Science and Engineering · January 1, 2023
The heterogeneous vehicle routing problem with time windows (HVRPTW) employs various vehicles with different capacities to serve upcoming pickup and delivery orders. We introduce a HVRPTW variant for reflecting the practical needs of crowd-shipping by cons ...
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Conference2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 · January 1, 2023
The present study provides an analysis on the characteristics of single-objective optimization benchmark problems as well as the algorithms used to solve them. The target optimization domain involves the CEC competitions, each consisting a set of mathemati ...
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ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2022
This work utilizes Algorithm Selection for solving the Team Orienteering Problem (TOP). The TOP is an NP-hard combinatorial optimization problem in the routing domain. This problem has been modelled with various extensions to address different real-world p ...
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Conference2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2022 · January 1, 2022
The present study introduces two methods for constructing portfolios of low-level heuristics, to be used by Selection Hyper-heuristics to solve Protein Structure Prediction with the 2D HP model. Protein Structure Prediction is useful and practical for vari ...
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ConferenceProceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 · January 1, 2022
The present study introduces algorithm selection on selection hyper-heuristics. Hyper-heuristics are known as problem-independent methods utilized to solve different instances from varying problem domains. In the literature, there has been effective hyper- ...
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ConferenceProceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 · January 1, 2022
The present work utilizes Algorithm Selection for automatically specifying the parameter tuning method for a given tuning task. The idea of parameter tuning is motivated by the premature algorithm designs and their sub-optimal or poor parameter value choic ...
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Journal ArticleIEEE transactions on cybernetics · September 2021
The gate assignment problem (GAP) aims at assigning gates to aircraft considering operational efficiency of airport and satisfaction of passengers. Unlike the existing works, we model the GAP as a bi-objective constrained optimization problem. The total wa ...
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Chapter · January 1, 2021
Algorithm design is a general task for any problem-solving scenario. For Search and Optimization, this task becomes rather challenging due to the immense algorithm design space. Those existing design options are usually traversed to devise algorithms by th ...
Full textCite

Conference2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings · January 1, 2021
The present paper introduces a benchmark set reduction strategy that can degrade the experimental evaluation cost for the algorithmic studies. Algorithm design is an iterative development process within in a test-revise loop. Starting a devised algorithm's ...
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ConferenceLearning and Intelligent Optimization · 2021
The present study applies Algorithm Selection (AS) to Adaptive Operator Selection (AOS) for further improving the performance of the AOS methods. AOS aims at delivering high performance in solving a given problem through combining the strengths of multiple ...
Cite

Conference2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings · January 1, 2021
The present work applies Algorithm Selection for automatically determining the best energy functions for search algorithms on Protein Structure Prediction. Protein Structure Prediction is a critical problem concerned with exploring the structure of a prote ...
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Conference2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings · January 1, 2021
The present study aims at generating heuristics for Protein Structure Prediction represented in the 2D HP model. Protein Structure Prediction is about determining the 3-dimensional form of a protein from a given amino acid sequence. The resulting structure ...
Full textCite

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2019
The present work accommodates active matrix completion to generate cheap and informative incomplete algorithm selection datasets. Algorithm selection is being used to detect the best possible algorithm(s) for a given problem ((formula presented) instance). ...
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Chapter · January 1, 2019
In this paper, we study the bundle design problem for offering personalized bundles of services using historical consumer redemption data. The problem studied here is for an operator managing multiple service providers, each responsible for an attraction, ...
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Journal ArticleJournal of Heuristics · June 1, 2018
Many real-world problems are composed of several interacting components. In order to facilitate research on such interactions, the Traveling Thief Problem (TTP) was created in 2013 as the combination of two well-understood combinatorial optimization proble ...
Full textCite

Conference2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings · July 5, 2017
Algorithm selection has been studied to specify the best possible algorithm(s) for a given problem instance. One of the major drawbacks of the algorithm selection methods is their need for the performance data. The performance data involves the performance ...
Full textCite

Chapter · January 1, 2024
Electrical and Electronic Equipment (EEE) has evolved into a gateway for accessing technological innovations. However, EEE imposes substantial pressure on the environment due to the shortened life cycles. E-waste encompasses discarded EEE and its component ...
Full textCite

Journal ArticleScientific reports · May 2023
The present study investigates the use of algorithm selection for automatically choosing an algorithm for any given protein-ligand docking task. In drug discovery and design process, conceptualizing protein-ligand binding is a major problem. Targeting this ...
Full textCite

Chapter · January 1, 2023
The present study applies Algorithm Selection to automatically specify the suitable algorithms for Large-Scale Multi-objective Optimization. Algorithm Selection has known to benefit from the strengths on multiple algorithm rather than relying one. This tra ...
Full textCite

Conference2023 IEEE Congress on Evolutionary Computation, CEC 2023 · January 1, 2023
The present study utilizes neural network to perform heuristic selection in selection hyper-heuristics. Selection hyper-heuristics are problem-independent solvers, preferably benefited for tackling a wide range of search and optimization problems. Unlike t ...
Full textCite

ConferenceIEEE International Conference on Automation Science and Engineering · January 1, 2023
The heterogeneous vehicle routing problem with time windows (HVRPTW) employs various vehicles with different capacities to serve upcoming pickup and delivery orders. We introduce a HVRPTW variant for reflecting the practical needs of crowd-shipping by cons ...
Full textCite

Conference2023 IEEE Symposium Series on Computational Intelligence, SSCI 2023 · January 1, 2023
The present study provides an analysis on the characteristics of single-objective optimization benchmark problems as well as the algorithms used to solve them. The target optimization domain involves the CEC competitions, each consisting a set of mathemati ...
Full textCite

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2022
This work utilizes Algorithm Selection for solving the Team Orienteering Problem (TOP). The TOP is an NP-hard combinatorial optimization problem in the routing domain. This problem has been modelled with various extensions to address different real-world p ...
Full textCite

Conference2022 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2022 · January 1, 2022
The present study introduces two methods for constructing portfolios of low-level heuristics, to be used by Selection Hyper-heuristics to solve Protein Structure Prediction with the 2D HP model. Protein Structure Prediction is useful and practical for vari ...
Full textCite

ConferenceProceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 · January 1, 2022
The present study introduces algorithm selection on selection hyper-heuristics. Hyper-heuristics are known as problem-independent methods utilized to solve different instances from varying problem domains. In the literature, there has been effective hyper- ...
Full textCite

ConferenceProceedings of the 2022 IEEE Symposium Series on Computational Intelligence, SSCI 2022 · January 1, 2022
The present work utilizes Algorithm Selection for automatically specifying the parameter tuning method for a given tuning task. The idea of parameter tuning is motivated by the premature algorithm designs and their sub-optimal or poor parameter value choic ...
Full textCite

Journal ArticleIEEE transactions on cybernetics · September 2021
The gate assignment problem (GAP) aims at assigning gates to aircraft considering operational efficiency of airport and satisfaction of passengers. Unlike the existing works, we model the GAP as a bi-objective constrained optimization problem. The total wa ...
Full textCite

Chapter · January 1, 2021
Algorithm design is a general task for any problem-solving scenario. For Search and Optimization, this task becomes rather challenging due to the immense algorithm design space. Those existing design options are usually traversed to devise algorithms by th ...
Full textCite

Conference2021 IEEE Congress on Evolutionary Computation, CEC 2021 - Proceedings · January 1, 2021
The present paper introduces a benchmark set reduction strategy that can degrade the experimental evaluation cost for the algorithmic studies. Algorithm design is an iterative development process within in a test-revise loop. Starting a devised algorithm's ...
Full textCite

ConferenceLearning and Intelligent Optimization · 2021
The present study applies Algorithm Selection (AS) to Adaptive Operator Selection (AOS) for further improving the performance of the AOS methods. AOS aims at delivering high performance in solving a given problem through combining the strengths of multiple ...
Cite

Conference2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings · January 1, 2021
The present work applies Algorithm Selection for automatically determining the best energy functions for search algorithms on Protein Structure Prediction. Protein Structure Prediction is a critical problem concerned with exploring the structure of a prote ...
Full textCite

Conference2021 IEEE Symposium Series on Computational Intelligence, SSCI 2021 - Proceedings · January 1, 2021
The present study aims at generating heuristics for Protein Structure Prediction represented in the 2D HP model. Protein Structure Prediction is about determining the 3-dimensional form of a protein from a given amino acid sequence. The resulting structure ...
Full textCite

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2019
The present work accommodates active matrix completion to generate cheap and informative incomplete algorithm selection datasets. Algorithm selection is being used to detect the best possible algorithm(s) for a given problem ((formula presented) instance). ...
Full textCite

Chapter · January 1, 2019
In this paper, we study the bundle design problem for offering personalized bundles of services using historical consumer redemption data. The problem studied here is for an operator managing multiple service providers, each responsible for an attraction, ...
Full textCite

Journal ArticleJournal of Heuristics · June 1, 2018
Many real-world problems are composed of several interacting components. In order to facilitate research on such interactions, the Traveling Thief Problem (TTP) was created in 2013 as the combination of two well-understood combinatorial optimization proble ...
Full textCite

Conference2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings · July 5, 2017
Algorithm selection has been studied to specify the best possible algorithm(s) for a given problem instance. One of the major drawbacks of the algorithm selection methods is their need for the performance data. The performance data involves the performance ...
Full textCite

Journal ArticleArtificial Intelligence · March 1, 2017
Algorithm selection (AS), selecting the algorithm best suited for a particular problem instance, is acknowledged to be a key issue to make the best out of algorithm portfolios. This paper presents a collaborative filtering approach to AS. Collaborative fil ...
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ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2017
The present paper proposes a Greedy based Pareto Local Search (GB-PLS) algorithm for the bi-objective robust airport gate assignment problem (bRAGAP). The bRAGAP requires to minimize the total passenger walking distance and the total robust cost of gate as ...
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ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2017
The concrete delivery problem (CDP) is an NP-hard, real world combinatorial optimization problem. The CDP involves tightly interrelated routing and scheduling constraints that have to be satisfied by considering the tradeoff between production and distribu ...
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ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2017
The present paper offers an analysis strategy to examine benchmark sets of combinatorial search problems. Experimental analysis has been widely used to compare a set of algorithms on a group of instances from such problem domains. These studies mostly focu ...
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ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2016
Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using ...
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ConferenceCommunications in Computer and Information Science · January 1, 2016
Selection hyper-heuristics are high level search methodologies which control a set of low level heuristics while solving a given problem. Move acceptance is a crucial component of selection hyperheuristics, deciding whether to accept or reject a new soluti ...
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Journal ArticleJournal of the Operational Research Society · May 20, 2015
The present study investigates the performance of heuristics while solving problems with routing and rostering characteristics. The target problems include scheduling and routing home care, security and maintenance personnel. In analysing the behaviour of ...
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ConferenceAAAI Workshop - Technical Report · January 1, 2015
Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using ...
Cite

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2015Full textCite

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2015
This paper introduces an automated approach called OSCAR that combines algorithm portfolios and online algorithm selection. The goal of algorithm portfolios is to construct a subset of algorithms with diverse problem solving capabilities. The portfolio is ...
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ConferencePATAT 2014 - Proceedings of the 10th International Conference on the Practice and Theory of Automated Timetabling · January 1, 2014
The patrol scheduling problem is concerned with assigning security teams to different stations for distinct time intervals while respecting a limited number of contractual constraints. The objective is to minimise the total distance travelled while maximis ...
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ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · January 1, 2014
Over the last decade, several algorithms for process discovery and process conformance have been proposed. Still, it is well-accepted that there is no dominant algorithm in any of these two disciplines, and then it is often difficult to apply them successf ...
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ConferenceGECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference · January 1, 2014
The present study introduces an automated mechanism to build algorithm portfolios for memetic algorithms. The objective is to determine an algorithm set involving combinations of crossover, mutation and local search operators based on their past performanc ...
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Conference2013 13th UK Workshop on Computational Intelligence, UKCI 2013 · December 31, 2013
A hyper-heuristic is a high level methodology which performs search over the space of heuristics each operating on the space of solutions to solve hard computational problems. This search process is based on either generation or selection of low level heur ...
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Journal ArticleApplied Soft Computing Journal · January 1, 2013
The present study concentrates on the generality of selection hyper-heuristics across various problem domains with a focus on different heuristic sets in addition to distinct experimental limits. While most hyper-heuristic research employs the term general ...
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Journal ArticleJournal of Scheduling · January 1, 2013
This study provides a new hyper-heuristic design using a learning-based heuristic selection mechanism together with an adaptive move acceptance criterion The selection process was supported by an online heuristic subset selection strategy In addition, a pa ...
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ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · October 30, 2012
The present study proposes a new selection hyper-heuristic providing several adaptive features to cope with the requirements of managing different heuristic sets. The approach suggested provides an intelligent way of selecting heuristics, determines effect ...
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ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) · September 24, 2012
The present study investigates the effect of heuristic sets on the performance of several selection hyper-heuristics. The performance of selection hyper-heuristics is strongly dependant on low-level heuristic sets employed for solving target problems. Ther ...
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Journal ArticleJournal of Heuristics · June 1, 2012
We present one general high-level hyper-heuristic approach for addressing two timetabling problems in the health care domain: the patient admission scheduling problem and the nurse rostering problem. The complex combinatorial problem of patient admission s ...
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Journal ArticleAnnals of Operations Research · January 1, 2012
Automating the neighbourhood selection process in an iterative approach that uses multiple heuristics is not a trivial task. Hyper-heuristics are search methodologies that not only aim to provide a general framework for solving problem instances at differe ...
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Conference2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 · December 1, 2010
A hyper-heuristic performs search over a set of other search mechanisms. During the search, it does not require any problem-dependent data. This structure makes hyper-heuristics problem-independent indirect search mechanisms. In this study, we propose a le ...
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Journal ArticleInternational Journal of Applied Metaheuristic Computing · January 1, 2010
Hyper-heuristics can be identified as methodologies that search the space generated by a finite set of low level heuristics for solving search problems. An iterative hyper-heuristic framework can be thought of as requiring a single candidate solution an ...
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