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A Transdisciplinary Approach to Enhancing Online Engineering Education Through Learning Analytics Masikini Lugoma , Lethuxolo Yende , Pule Dikgwatlhe , Akhona Mkonde , Rorisang Thage , Lucky Maseko , Ngonidzashe Chimwani (pages: 1-6) AI Disruptions in Higher Education: Evolutionary Change, Not Revolutionary Overthrow Cristo Leon , James Lipuma , Maximus Rafla (pages: 7-18) Education, Research, and Methodology: A Transdisciplinary Cybernetic Whole Nagib Callaos , Cristo Leon (pages: 19-33) Enhancing Educational Effectiveness Through Transdisciplinary Practice: The ETCOP Model Birgit Oberer , Alptekin Erkollar , Andreas Kropfberger (pages: 34-40) From Instruction to Interaction: Reflexive Learning Design for Cross-Generational Engagement at the Workplace Gita Aulia Nurani , Ya-Hui Lee (pages: 41-44) GIS in Aquatic Animal Health Surveillance: A Transdisciplinary eLearning Initiative Integrating Education, Research, and Methodology (The Aquae Strength Project) Eleonora Franzago , Rodrigo Macario , Matteo Mazzucato , Federica Sbettega , Manuela Cassani , Guido Ricaldi , Francesco Bissoli , Anna Nadin , Fabrizio Personeni , Manuela Dalla Pozza , Grazia Manca , Nicola Ferré (pages: 45-50) Reflexivity as a Compass: The European AI Act and Its Implications for U.S. Higher Education Institutions Jasmin Cowin (pages: 51-56) Required General Education Program Evaluation: Bridging the Gap Between Educators and Administrators James Lipuma , Cristo Leon , Jeremy Reich (pages: 57-61) Researching Ourselves Jeremy Horne (pages: 62-72) The Self-Aware, Reflective Learner: Fostering Metacognitive Awareness and Reflexivity in Undergraduates Through Service-Learning Genejane Adarlo (pages: 73-81)
ABSTRACT
A Niche Sharing Scheme-based Co-evolutionary Particle Swarm Optimization Algorithm for Flow Shop Scheduling Problem
By taking advantage of niche sharing scheme,we propose a
novel co-evolutionary particle swarm optimization algorithm
(NCPSO) to solve permutation flow shop scheduling problem.
As the core of this algorithm, niche sharing scheme maximizes
the diversity of population and hence improves the quality of
individuals. To evaluate the performance of the proposed
algorithm, we have use eight Taillard instances with different
sizes to extensive experiment and results clearly shown that the
solutions found by NCPSO algorithm outperform those by
Particle Swarm Optimization (PSO), Genetic Algorithm (GA)
and Cooperative Particle Swarm Optimization (CPSO).
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