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Moreover, in multi-objective optimisation, the correlation between objective functions is known to affect search space structure and algorithm performance. Considering the recent success of automatic algorithm configuration (AAC) techniques for the design of multi-objective optimisation algorithms, this raises two interesting questions: what is the impact of correlation between optimisation objectives on (1) the efficacy of different AAC approaches and (2) on the optimised algorithm designs obtained from these automated approaches? In this work, we study these questions for multi-objective local search algorithms (MOLS) for three well-known bi-objective permutation problems, using two single-objective AAC approaches and one multiobjective approach. Our empirical results clearly show that overall, multi-objective AAC is the most effective approach for the automatic configuration of the highly parametric MOLS framework, and that there is no systematic impact of the degree of correlation on the relative performance of the three AAC approaches. We also find that the best-performing configurations differ, depending on the correlation between objectives and the size of the problem instances to be solved, providing further evidence for the usefulness of automatic configuration of multiobjective optimisation algorithms.","publication_name":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","grobid_abstract_attachment_id":"96686830"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Automatic Configuration of Bi-Objective Optimisation Algorithms: Impact of Correlation Between Objectives","broadcastable":false,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [9335826]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; 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Pardo</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32253676" href="https://independent.academia.edu/JuanPantrigo">Juan Pantrigo</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="32279447" href="https://urjc.academia.edu/AbrahamDuarte">Abraham Duarte</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Multi-objective variable neighborhood search: an application to combinatorial optimization problems","attachmentId":45744646,"attachmentType":"pdf","work_url":"https://www.academia.edu/13045188/Multi_objective_variable_neighborhood_search_an_application_to_combinatorial_optimization_problems","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/13045188/Multi_objective_variable_neighborhood_search_an_application_to_combinatorial_optimization_problems"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="23080321" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/23080321/Automatic_Design_of_Evolutionary_Algorithms_for_Multi_Objective_Combinatorial_Optimization">Automatic Design of Evolutionary Algorithms for Multi-Objective Combinatorial Optimization</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="1160684" href="https://ulb.academia.edu/LeonardoBezerra">Leonardo Bezerra</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="42782172" href="https://independent.academia.edu/ThomasSt%C3%BCtzle">Thomas Stützle</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Lecture Notes in Computer Science, 2014</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Automatic Design of Evolutionary Algorithms for Multi-Objective Combinatorial Optimization","attachmentId":43582286,"attachmentType":"pdf","work_url":"https://www.academia.edu/23080321/Automatic_Design_of_Evolutionary_Algorithms_for_Multi_Objective_Combinatorial_Optimization","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/23080321/Automatic_Design_of_Evolutionary_Algorithms_for_Multi_Objective_Combinatorial_Optimization"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="58418508" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/58418508/On_Algorithmic_Descriptions_and_Software_Implementations_for_Multi_objective_Optimisation_A_Comparative_Study">On Algorithmic Descriptions and Software Implementations for Multi-objective Optimisation: A Comparative Study</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="54193993" href="https://dmu.academia.edu/FerranteNeri">Ferrante Neri</a></div><p class="ds-related-work--metadata ds2-5-body-xs">SN Computer Science</p><p class="ds-related-work--abstract ds2-5-body-sm">Multi-objective optimisation is a prominent subfield of optimisation with high relevance in real-world problems, such as engineering design. Over the past 2 decades, a multitude of heuristic algorithms for multi-objective optimisation have been introduced and some of them have become extremely popular. Some of the most promising and versatile algorithms have been implemented in software platforms. This article experimentally investigates the process of interpreting and implementing algorithms by examining multiple popular implementations of three well-known algorithms for multi-objective optimisation. We observed that official and broadly employed software platforms interpreted and thus implemented the same heuristic search algorithm differently. These different interpretations affect the algorithmic structure as well as the software implementation. Numerical results show that these differences cause statistically significant differences in performance.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"On Algorithmic Descriptions and Software Implementations for Multi-objective Optimisation: A Comparative Study","attachmentId":72838795,"attachmentType":"pdf","work_url":"https://www.academia.edu/58418508/On_Algorithmic_Descriptions_and_Software_Implementations_for_Multi_objective_Optimisation_A_Comparative_Study","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/58418508/On_Algorithmic_Descriptions_and_Software_Implementations_for_Multi_objective_Optimisation_A_Comparative_Study"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":96686830,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":96686830,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_96686830" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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href="https://independent.academia.edu/SaulMartinez101">Saul Martinez</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2012</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A direct local search mechanism for decomposition-based multi-objective evolutionary algorithms","attachmentId":91110131,"attachmentType":"pdf","work_url":"https://www.academia.edu/86721585/A_direct_local_search_mechanism_for_decomposition_based_multi_objective_evolutionary_algorithms","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" 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class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-related-work-sidebar-card" data-collection-position="7" data-entity-id="55445686" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/55445686/Multi_objective_combinatorial_optimization_problems_A_survey">Multi-objective combinatorial optimization problems: A survey</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="36927135" href="https://independent.academia.edu/JacquesTeghem">Jacques Teghem</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Multi-Criteria Decision Analysis, 1994</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline 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