Distributed Cognition As the Basis for Adaptation and Homeostasis In
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Application of the Firefly Algorithm for Optimal Production and Demand Forecasting at Selected Industrial Plant
Open Journal of Business and Management, 2020, 8, 2451-2459 https://www.scirp.org/journal/ojbm ISSN Online: 2329-3292 ISSN Print: 2329-3284 Application of the Firefly Algorithm for Optimal Production and Demand Forecasting at Selected Industrial Plant Abdulhadi Altherwi Industrial and Systems Engineering Department, Oakland University, Rochester, MI, USA How to cite this paper: Altherwi, A. (2020). Abstract Application of the Firefly Algorithm for Optimal Production and Demand Fore- Many production companies continue to face financial difficulties. The main casting at Selected Industrial Plant. Open purpose of this paper is to present an effective method for these companies to Journal of Business and Management, 8, maximize profits and minimize production costs. The problem presented 2451-2459. https://doi.org/10.4236/ojbm.2020.86151 here is initially developed as a linear programming model. To achieve the best results, the firefly algorithm (FA) is applied to solve the model and obtain an Received: October 15, 2020 optimum solution. In order to test the efficiency of the algorithm, Lindo Accepted: November 13, 2020 software is used, and the results of both algorithms are compared. A sensitiv- Published: November 16, 2020 ity analysis is applied to determine which products a company should pro- Copyright © 2020 by author(s) and duce in order to maximize profits. The result reveals that the FA, when com- Scientific Research Publishing Inc. pared with Lindo, can help achieve maximum profits by producing only one This work is licensed under the Creative product, thus minimizing production costs. For demand forecasting, the Commons Attribution International License (CC BY 4.0). -
An Improved Bees Algorithm Local Search Mechanism for Numerical Dataset
An Improved Bees Algorithm Local Search Mechanism for Numerical dataset Prepared By: Aras Ghazi Mohammed Al-dawoodi Supervisor: Dr. Massudi bin Mahmuddin DISSERTATION SUBMITTED TO THE AWANG HAD SALLEH GRADUATE SCHOOL OF COMPUTING UUM COLLEGE OF ARTS AND SCIENCES UNIVERSITI UTARA MALAYSIA IN PARITIAL FULFILLMENT OF THE REQUIREMENT FOR THE DEGREE OF MASTER IN (INFORMATION TECHNOLOGY) 2014 - 2015 Permission to Use In presenting this dissertation report in partial fulfilment of the requirements for a postgraduate degree from University Utara Malaysia, I agree that the University Library may make it freely available for inspection. I further agree that permission for the copying of this report in any manner, in whole or in part, for scholarly purpose may be granted by my supervisor(s) or, in their absence, by the Dean of Awang Had Salleh Graduate School of Arts and Sciences. It is understood that any copying or publication or use of this report or parts thereof for financial gain shall not be allowed without my written permission. It is also understood that due recognition shall be given to me and to University Utara Malaysia for any scholarly use which may be made of any material from my report. Requests for permission to copy or to make other use of materials in this project report, in whole or in part, should be addressed to: Dean of Awang Had Salleh Graduate School of Arts and Sciences UUM College of Arts and Sciences University Utara Malaysia 06010 UUM Sintok i Abstrak Bees Algorithm (BA), satu prosedur pengoptimuman heuristik, merupakan salah satu teknik carian asas yang berdasarkan kepada aktiviti pencarian makanan lebah. -
Application of the Firefly Algorithm for Solving the Economic Emissions
Hindawi Publishing Corporation International Journal of Combinatorics Volume 2011, Article ID 523806, 23 pages doi:10.1155/2011/523806 Research Article Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem Theofanis Apostolopoulos and Aristidis Vlachos Department of Informatics, University of Piraeus, 80 Karaoli and Dimitriou Street, 18534 Piraeus, Greece Correspondence should be addressed to Aristidis Vlachos, [email protected] Received 30 August 2010; Accepted 14 November 2010 Academic Editor: Hajo Broersma Copyright q 2011 T. Apostolopoulos and A. Vlachos. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Efficient and reliable power production is necessary to meet both the profitability of power systems operations and the electricity demand, taking also into account the environmental concerns about the emissions produced by fossil-fuelled power plants. The economic emission load dispatch problem has been defined and applied in order to deal with the optimization of these two conflicting objectives, that is, the minimization of both fuel cost and emission of generating units. This paper introduces and describes a solution to this famous problem using a new metaheuristic nature-inspired algorithm, called firefly algorithm, which was developed by Dr. Xin-She Yang at Cambridge University in 2007. A general formulation of this algorithm is presented together with an analytical mathematical modeling to solve this problem by a single equivalent objective function. The results are compared with those obtained by alternative techniques proposed by the literature in order to show that it is capable of yielding good optimal solutions with proper selection of control parameters. -
GB-Human Computation Handbook
From Human Computation to the Global Brain: the self-organization of distributed intelligence Francis Heylighen Global Brain Institute Vrije Universiteit Brussel Introduction The present chapter wishes to investigate the wider context of human computation, viewing it as merely one approach within the broad domain of distributed human-computer symbiosis. The multifarious developments in the “social” Internet have shown the great potential of large-scale col- laborative systems that involve both people and the various information and communication technologies (ICT) that process, store and distribute data. Here, I wish to explore this development in the broadest sense, as the self-organization of a distributed intelligence system at the planetary level—a phenomenon that has been called the “global brain”. To get there, I will first define and illustrate the fundamental concept of distributed intelligence. Then I will review how such an intelligent net- work emerges and grows through a combination of self-organization and design. Finally, I will sketch some potential applications of the anticipated global brain. Human-computer complementarity The rationale for human computation is that people have certain intrinsic skills that are difficult to reproduce in computer programs. A computation system that requires those skills must therefore include people as informa- tion-processing agents. Thus, in human computation, people and comput- ers are supposed to work together synergetically, the one complementing the other. The reason for this complementarity lies in the fact that humans and com- puters process information in very different ways. Computers excel at ac- curately storing and retrieving discrete items, such as numbers or strings of characters. -
Firefly Algorithm Applied to Integer Programming Problems
Recent Advances in Mathematics Firefly Algorithm Applied to Integer Programming Problems Nebojsa BACANIN, Ivona BRAJEVIC, Milan TUBA Faculty of Computer Science Megatrend University Belgrade Bulevar umetnosti 29, N. Belgrade SERBIA [email protected], [email protected], [email protected], Abstract: - Firefly algorithm is a recently added member of the swarm intelligence heuristics family. In this paper the firefly algorithm is adjusted and applied to integer programming problems. In order to deal with integer programming problems, firefly algorithm rounds the parameter values to the closest integer after producing new solutions. The performance of firefly algorithm is tested on seven problems widely used in the literature. Artificial bee colony algorithm is also implemented for comparison with the results of the firefly algorithm. Experimental results show that the firefly algorithm proved to be superior in almost all tested problems. Key-Words: - Firefly algorithm, Optimization metaheuristics, Integer programming, Swarm intelligence 1 Introduction Delaunay triangulation of the free configuration Linear programming optimization can find optimal space [3] are also solvable by integer programming solution to problems with hundreds of thousands of method. The entire class of problems referred to as constraints and variables. Modeling strength and sequencing, scheduling and routing is inherently solvability makes linear programming technique integer programs. This class of problems might for applicable in real life problems. Integer example deal with the scheduling of students and programming is a form of mathematical classrooms in such a way that the number of optimization program where some or all employed students who cannot take their first choice of classes variables are required to have integer values. -
Comparison of Hybrid Firefly Algorithms for Power Allocation in a TV White Space Network
International Journal of Computer Applications (0975 – 8887) Volume 178 – No. 38, August 2019 Comparison of Hybrid Firefly Algorithms for Power Allocation in a TV White Space Network Kennedy K. Ronoh George Kamucha Tonny K. Omwansa School of Computing and Department of Electrical and School of Computing and Informatics Information Engineering Informatics University of Nairobi University of Nairobi University of Nairobi Nairobi, Kenya Nairobi, Kenya Nairobi, Kenya ABSTRACT 1GHz spectrum. TV white spaces (TVWS) can be used by Secondary Users Regulatory authorities worldwide have mandated the use of (SUs) through Dynamic Spectrum Access (DSA) as long as geo-location database (GLDB) for protection of incumbent they do not cause harmful interference to Primary Users users in TVWS network. GLDB is used by a SU or White (PUs). Due spectrum scarcity, there is increasing demand for Space Device (WSD) to find the set of frequency channels DSA. When there is a high density of SUs in a TVWS that can be used on a secondary basis at a given area and at network such as cellular access to TVWS, problem of any given time [5], [6], [7]. GLDB is populated through the interference among SUs will arise. Possibility of harmful use of a propagation model. The database contains estimated interference to PUs may also arise. Optimization of power power levels of PUs for any point in a particular region of allocation is therefore necessary to reduce the level of interest. The WSD, which has a Cognitive Radio System interference among SUs and to protect PUs against harmful (CRS), queries a central database. -
Supported Collaborative Learning at the Workplace
Computer-Supported Collaborative Learning Series Sean P. Goggins Isa Jahnke Volker Wulf Editors Computer- Supported Collaborative Learning at the Workplace CSCL@Work Computer-Supported Collaborative Learning at the Workplace COMPUTER-SUPPORTED COLLABORATIVE LEARNING SERIES Series Editors: Christopher Hoadley, New York University, New York, USA Naomi Miyake, Chukyo University, Aichi, Japan Editorial Board: Michael Baker, CNRS & Université Lumière Lyon, France Carl Bereiter, Ontario Institute for Studies in Education, Canada Yrjö Engeström, University of Helsinki, Finland Gerhard Fischer, University of Colorado, U.S.A. H. Ulrich Hoppe, University of Duisburg-Essen, Germany Timothy Koschmann, Southern Illinois University, U.S.A. Claire O’Malley, University of Nottingham, U.K. Roy Pea, SRI International, U.S.A. Clotilde Pontecorovo, University ‘La Sapienza’, Italy Jeremy Roschelle, SRI International, U.S.A. Daniel Suthers, University of Hawaii, U.S.A. The Computer-Supported Collaborative Learning Book Series is for people working in the CSCL fi eld. The scope of the series extends to ‘collaborative learning’ in its broadest sense; the term is used for situations ranging from two individuals performing a task together, during a short period of time, to groups of 200 students following the same course and interacting via electronic mail. This variety also concerns the computational tools used in learning: elaborated graphical whiteboards support peer interaction, while more rudimentary textbased discussion forums are used for large group interaction. The series will integrate issues related to CSCL such as collaborative problem solving, collaborative learning without computers, negotiation patterns outside collaborative tasks, and many other relevant topics. It will also cover computational issues such as models, algorithms or architectures which support innovative functions relevant to CSCL systems. -
Human Enhancement Technologies and Our Merger with Machines
Human Enhancement and Technologies Our Merger with Machines Human • Woodrow Barfield and Blodgett-Ford Sayoko Enhancement Technologies and Our Merger with Machines Edited by Woodrow Barfield and Sayoko Blodgett-Ford Printed Edition of the Special Issue Published in Philosophies www.mdpi.com/journal/philosophies Human Enhancement Technologies and Our Merger with Machines Human Enhancement Technologies and Our Merger with Machines Editors Woodrow Barfield Sayoko Blodgett-Ford MDPI • Basel • Beijing • Wuhan • Barcelona • Belgrade • Manchester • Tokyo • Cluj • Tianjin Editors Woodrow Barfield Sayoko Blodgett-Ford Visiting Professor, University of Turin Boston College Law School Affiliate, Whitaker Institute, NUI, Galway USA Editorial Office MDPI St. Alban-Anlage 66 4052 Basel, Switzerland This is a reprint of articles from the Special Issue published online in the open access journal Philosophies (ISSN 2409-9287) (available at: https://www.mdpi.com/journal/philosophies/special issues/human enhancement technologies). For citation purposes, cite each article independently as indicated on the article page online and as indicated below: LastName, A.A.; LastName, B.B.; LastName, C.C. Article Title. Journal Name Year, Volume Number, Page Range. ISBN 978-3-0365-0904-4 (Hbk) ISBN 978-3-0365-0905-1 (PDF) Cover image courtesy of N. M. Ford. © 2021 by the authors. Articles in this book are Open Access and distributed under the Creative Commons Attribution (CC BY) license, which allows users to download, copy and build upon published articles, as long as the author and publisher are properly credited, which ensures maximum dissemination and a wider impact of our publications. The book as a whole is distributed by MDPI under the terms and conditions of the Creative Commons license CC BY-NC-ND. -
Synchronization of Fireflies Can Improve Or Inspire Robotic Swarm
elligenc International Journal of Swarm nt e I an rm d a E w v S o f l u o t l i o a n n a r u r Intelligence and Evolutionary y o C J l o a m n p ISSN:o 2090-4908 i t u a t a n t r i o e t n I n Computation Editorial Synchronization of Fireflies can Improve or Inspire Robotic Swarm Seelu Palai* Department of Computer Science, Parul University, Limda, Waghodia, Gujarat DESCRIPTION issue within the scientific community, many researchers believe Despite their simple brains, synchronized fireflies have that it helps fireflies for locating mates, protecting themselves something to show us about AI. A recent discovery on the from their predators and attracting their potential prey. within insect's amazing light shows could help researchers acquire fresh the firefly algorithm, the target function of a given optimization insight into swarm robotics. It seems, the synchronized fireflies' problem is related to this flashing light or candlepower which light displays are even more subtle than scientists realized, and helps the swarm of fireflies to maneuver to brighter and more it's to try to with the insect's three-dimensional positioning. They attractive locations so as to get efficient optimal solutions. found that fireflies behave differently after they are alone versus Multiple conflicting objectives arise naturally in most real-world in groups. In seems, synchronized fireflies what their neighbors combinatorial optimization problems. Several principles and do, rather than blinking consistent with any inherent rhythm. methods are developed and proposed for over a decade so as to Then they modify their blinking pattern to match those around resolve problems. -
Three Novel Quantum-Inspired Swarm Optimization Algorithms Using
www.nature.com/scientificreports OPEN Three novel quantum‑inspired swarm optimization algorithms using diferent bounded potential felds Manuel S. Alvarez‑Alvarado1*, Francisco E. Alban‑Chacón2, Erick A. Lamilla‑Rubio2, Carlos D. Rodríguez‑Gallegos3 & Washington Velásquez1 Based on the behavior of the quantum particles, it is possible to formulate mathematical expressions to develop metaheuristic search optimization algorithms. This paper presents three novel quantum‑ inspired algorithms, which scenario is a particle swarm that is excited by a Lorentz, Rosen–Morse, and Coulomb‑like square root potential felds, respectively. To show the computational efcacy of the proposed optimization techniques, the paper presents a comparative study with the classical particle swarm optimization (PSO), genetic algorithm (GA), and frefy algorithm (FFA). The algorithms are used to solve 24 benchmark functions that are categorized by unimodal, multimodal, and fxed‑ dimension multimodal. As a fnding, the algorithm inspired in the Lorentz potential feld presents the most balanced computational performance in terms of exploitation (accuracy and precision), exploration (convergence speed and acceleration), and simulation time compared to the algorithms previously mentioned. A deeper analysis reveals that a strong potential feld inside a well with weak asymptotic behavior leads to better exploitation and exploration attributes for unimodal, multimodal, and fxed‑multimodal functions. Gradient-based and Hessian-based algorithms are widely use in the literature to solve optimization problems in engineering. Tis is due to their computational efciency, which typically require little problem-specifc parameter tuning1. Te Gradient-based and Hessian-based algorithms employ iterative process that involves multivariate scalar function that packages all the information of the partial derivatives of the objective function (i.e., Gradient function or Hessian matrix) to reach the solution. -
Applying Firefly Algorithm to Solve the Problem of Balancing Curricula
(IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 10, No. 1, 2019 Applying FireFly Algorithm to Solve the Problem of Balancing Curricula 1* 2* 3 4 5 6 Jose´ Miguel Rubio , Cristian L. Vidal-Silva , Ricardo Soto , Erika Madariaga , Franklin Johnson , Luis Carter 1 ´Area Acad´emica de Inform´atica y Telecomunicaciones, Universidad Tecnol´ogica de Chile INACAP, Santiago, Chile 2Ingenier´ıa Civil Inform´atica, Escuela de Ingenier´ıa, Universidad Vi˜na del Mar, Vi˜na del Mar, Chile 3Escuela de Ingenier´ıa Inform´atica, Facultad de Ingenier´ıa, Pontificia Universidad Cat´olica de Valpara´ıso, Valpara´ıso, Chile 4Ingenier´ıa Inform´atica, Facultad de Ingenier´ıa, Ciencia y Tecnolog´ıa, Universidad Bernardo O’Higgins, Santiago, Chile 5Depto. Disciplinario de Computaci´on e Inform´atica, Facultad de Ingenier´ıa, Universidad de Playa Ancha, Valpara´so, Chile 6Ingenier´ıa Civil Industrial, Facultad de Ingenier´ıa, Universidad Aut´onoma de Chile, Talca, Chile Abstract—The problem of assigning a balanced academic the paradigm of programming with restrictions and hybrid curriculum to academic periods of a curriculum, that is, the algorithms using genetic algorithms, collaboration schemes, balancing curricula, represents a traditional challenge for every and local searches, among other techniques. educational institution which look for a match among students and professors. This article proposes a solution for the balancing The present work focuses on solving the test instances curricula problem using an optimization technique based on the recognized by the CSPLib [1], and a few real situations of attraction of fireflies (FA) meta-heuristic. We perform a set of test the problem in the study programs of the computer area of and real instances to measure the performance of our solution two Chilean universities. -
Distributed Cognition in Classical Antiquity Reveals Diverse Notions of Distributed Cognition in the Early Greek and Roman Worlds
Edited by Miranda Anderson, THE EDINBURGH HISTORY OF DISTRIBUTED COGNITION Douglas Cairns and THE EDINBURGH HISTORY OF DISTRIBUTED COGNITION Mark Sprevak ‘Once we look for it, distributed cognition is ubiquitous in classical antiquity. This book is a fascinating examination of the tools that made thinking easier and of the complex boundaries between the individual mind and the group.’ Ruth Scodel, University of Michigan Distributed Cognition in Classical Antiquity Reveals diverse notions of distributed cognition in the early Greek and Roman worlds This collection brings together eleven essays by international specialists in classical antiquity and provides a general and a period-specific introduction to distributed cognition and the cognitive humanities. The essays look at the ways in which cognition is explicitly or implicitly conceived of as distributed across brain, body and world in Greek and Roman technology, science and medicine, material culture, philosophy and literary studies. This exploratory work will be valuable across the humanities as it reveals the historical foundations of our theoretical and practical attempts to comprehend and optimise the distributed nature of human cognition. Miranda Anderson is a Research Fellow at the University of Edinburgh. Douglas Cairns is Professor of Classics in the University of Edinburgh. Mark Sprevak is Senior Lecturer in Philosophy at the University of Edinburgh. Distributed Cognition in Classical Antiquity Cover image: © János Kass, etching made for the illustration of Madách Imre’s Az ember tragédiája (Tragedy of Man), Egypt Cover design: Bekah Mackenzie and Stuart Dalziel Edited by Miranda Anderson, Douglas Cairns and Mark Sprevak 2 Distributed Cognition in Classical Antiquity Distributed Cognition in Classical Antiquity Edited by Miranda Anderson, Douglas Cairns and Mark Sprevak Edinburgh University Press is one of the leading university presses in the UK.