A hybrid simulated annealing for scheduling in dual-resource cellular manufacturing system considering worker movement

This paper presents a novel linear mathematical model for integrated cell formation and task scheduling in the cellular manufacturing system (CMS). It is suitable for the dual-resource constrained setting, such as garment process, component assembly, and electronics manufacturing. The model can handle the manufacturing project composing of some tasks with precedence constraints. It provides a method to assign the multi-skilled workers to appropriate machines. The workers are allowed to move among the machines such that the processing time of tasks might be reduced. A hybrid simulated annealing (HSA) is proposed to minimize the makespan of manufacturing project in the CMS. The approach combines the priority rule based heuristic algorithm (PRBHA) and revised forward recursion algorithm (RFRA) with conventional simulated annealing (SA). The result of extensive numerical experiments shows that the proposed HSA outperforms the conventional SA accurately and efficiently

Flexible job-shop scheduling with learning and forgetting effect by Multi-Agent System

The processing time of the machine is assumed fixed in several studies. In many real industrial applications, the processing time is affected by learning and forgetting effects. This research proposes a scheduling approach to support a manufacturing system under learning/forgetting effect. The approach is supported by a Multi-Agent System to perform the scheduling activities in a quasi-real-time and in general manufacturing systems. A simulation environment is developed to test the proposed approach and the results are compared with a benchmark model for evaluating several performance measures of the manufacturing system. The simulation results highlight how the proposed approach improves all the performance measures under different conditions of inter-arrival time, learning and forgetting rates. A complete Analysis of the Variance highlights the main effects on the performance measures to support the decision maker of the manufacturing system

The Team Size Paradox: Knowledge Transfer and Process Loss Effects on Team Formation

Teamwork has become a popular operational strategy applied as part of workforce management plans in manufacturing and service industries. Teamwork has been commonly used in organizations to pursue different goals such as increase business operations agility, boost company productivity, improve quality in operations, increase company flexibility, promote collaborative learning, hasten the learning process of novice workers during training, promote employee’s motivation, or in some cases as a necessary tool to perform specific operations that cannot be performed by individual workers. Previous work has shown that the application of a teamwork strategy as part of the organization workforce management plan can positively impact the organization outcomes via creativity, innovation, motivation and learning. However, there is also evidence that a teamwork strategy can have a significant negative impact on organizational outcomes if the strategy is not properly designed and implemented because of greater demands on cooperation, limitations in communication, conflicts among workers, and cognitive biases. The impact of the benefits and relative costs of teamwork as part of workforce management plans are mostly determined by the design and implementation of a teamwork strategy and by the specific task and organization in which the teamwork strategy is applied. Thus, the informed design of a teamwork strategy is necessary in order to obtain the maximum benefit of its implementation in organizations. The literature on teamwork has mainly focused on observational studies that facilitates the understanding of teamwork dynamics based on team composition and how these affect individuals and team performance. However, the translation of findings in these studies to operation research strategies for workforce management application has been limited. Specifically, studies that address workforce allocation when is applied a teamwork-based strategy implementation in organizations has received little attention in literature, while the consideration of team dynamics from both perspectives, gains and losses, simultaneously is still a gap in the literature of operation research for the study and development of workforce management plans. The goal of this dissertation is to reduce this gap, addressing the design of workforce management plans that considers the implementation of a teamwork strategy accounting for the gains and losses that arise from team dynamics. This work presents the exploration of the team formation process from the perspective of team size for learning-productivity environments. Workforce heterogeneity is considered through the modeling of individuals’ productivity as function of individual learning parameters. Team dynamics are incorporated in an individual productivity model by including learning by knowledge transfer, which accounts for the benefits in individual productivity that can be gain though the interaction of workers within the team, and by including process loss, which accounts for the losses in individual productivity that arise from demand in coordination, conflicts, motivation losses and communication challenges that arise in teams. The methodology used in the study centers on the use of simulation and explicit mathematical representations based on models in the literature. This dissertation 1) explores the jointly effects of human and organizational factors on system performance and their relevance to the worker-cell assignment problem, which demonstrates the value of considering these factors as part of the workforce planning process in a cellular manufacturing setting; 2) investigate the joint effects of knowledge transfer and the process loss on team performance resulting from the incorporation of additional workers into the work team and its implication on the optimal team size when considering different type of task structures; and 3) explores the team formation problem with the aim of characterizing optimal team size in a multiple work-team setting. This dissertation will serve as basis for the development of mathematical models to address the team formation problem as part of operation research applications considering individuals productivity gain and losses which results from team dynamic and provide insight to guide managers in making decisions about team design and teamwork strategy implementation

2020 GREAT Day Program

SUNY Geneseo’s Fourteenth Annual GREAT Day.https://knightscholar.geneseo.edu/program-2007/1014/thumbnail.jp

Using MapReduce Streaming for Distributed Life Simulation on the Cloud

Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp

A complex systems approach to education in Switzerland

The insights gained from the study of complex systems in biological, social, and engineered systems enables us not only to observe and understand, but also to actively design systems which will be capable of successfully coping with complex and dynamically changing situations. The methods and mindset required for this approach have been applied to educational systems with their diverse levels of scale and complexity. Based on the general case made by Yaneer Bar-Yam, this paper applies the complex systems approach to the educational system in Switzerland. It confirms that the complex systems approach is valid. Indeed, many recommendations made for the general case have already been implemented in the Swiss education system. To address existing problems and difficulties, further steps are recommended. This paper contributes to the further establishment complex systems approach by shedding light on an area which concerns us all, which is a frequent topic of discussion and dispute among politicians and the public, where billions of dollars have been spent without achieving the desired results, and where it is difficult to directly derive consequences from actions taken. The analysis of the education system's different levels, their complexity and scale will clarify how such a dynamic system should be approached, and how it can be guided towards the desired performance

Collective intelligence: creating a prosperous world at peace

XXXII, 612 p. ; 24 cmLibro ElectrónicoEn este documento se plantea un tema de interes general mas como lo es especificamente el tema de la evolucion de la sociedad en materia de industria y crecimiento de las actividades humanas en el aspecto de desarrollo de la creatividad enfocada a los mercadosedited by Mark Tovey ; foreword by Yochai Benkler (re-mixed by Hassan Masum) ; prefaces by Thomas Malone, Tom Atlee & Pierre Levy ; afterword by Paul Martin & Thomas Homer-Dixon.The era of collective intelligence has begun in earnest. While others have written about the wisdom of crowds, an army of Davids, and smart mobs, this collection of essays for the first time brings together fifty-five pioneers in the emerging discipline of collective intelligence. They provide a base of tools for connecting people, producing high-functioning teams, collaborating at multiple scales, and encouraging effective peer-production. Emerging models are explored for digital deliberative democracy, self-governance, legislative transparency, true-cost accounting, and the ethical use of open sources and methods. Collective Intelligence is the first of a series of six books, which will also include volumes on Peace Intelligence, Commercial Intelligence, Gift Intelligence, Cultural Intelligence, and Global Intelligence.Table of Contents Dedication i Publisher’s Preface iii Foreword by Yochai Benkler Remix Hassan Masum xi The Wealth of Networks: Highlights remixed Editor’s Preface xxi Table of Contents xxv A What is collective intelligence and what will we do 1 about it? (Thomas W. Malone, MIT Center for Collective Intelligence) B Co-Intelligence, collective intelligence, and conscious 5 evolution (Tom Atlee, Co-Intelligence Institute) C A metalanguage for computer augmented collective 15 intelligence (Prof. Pierre Lévy, Canada Research Chair in Collective Intelligence, FRSC) I INDIVIDUALS & GROUPS I-01 Foresight I-01-01 Safety Glass (Karl Schroeder, science fiction author 23 and foresight consultant) I-01-02 2007 State of the Future (Jerome C. Glenn & 29 Theodore J. Gordon, United Nations Millennium Project) I-02 Dialogue & Deliberation I-02-01 Thinking together without ego: Collective intelligence 39 as an evolutionary catalyst (Craig Hamilton and Claire Zammit, Collective-Intelligence.US) I-02-02 The World Café: Awakening collective intelligence 47 and committed action (Juanita Brown, David Isaacs and the World Café Community) I-02-03 Collective intelligence and the emergence of 55 wholeness (Peggy Holman, Nexus for Change, The Change Handbook) I-02-04 Knowledge creation in collective intelligence (Bruce 65 LaDuke, Fortune 500, HyperAdvance.com) I-02-05 The Circle Organization: Structuring for collective 75 wisdom (Jim Rough, Dynamic Facilitation & The Center for Wise Democracy) I-03 Civic Intelligence I-03-01 Civic intelligence and the public sphere (Douglas 83 Schuler, Evergreen State College, Public Sphere Project) I-03-02 Civic intelligence and the security of the homeland 95 (John Kesler with Carole and David Schwinn, IngeniusOnline) I-03-03 Creating a Smart Nation (Robert Steele, OSS.Net) 107 I-03-04 University 2.0: Informing our collective intelligence 131 (Nancy Glock-Grueneich, HIGHEREdge.org) I-03-05 Producing communities of communications and 145 foreknowledge (Jason “JZ” Liszkiewicz, Reconfigure.org) I-03-06 Global Vitality Report 2025: Learning to transform I-04 Electronic Communities & Distributed Cognition I-04-01 Attentional capital and the ecology of online social 163 conflict and think together effectively (Peter+Trudy networks (Derek Lomas, Social Movement Lab, Johnson-Lenz, Johnson-Lenz.com ) UCSD) I-04-02 A slice of life in my virtual community (Howard 173 Rheingold, Whole Earth Review, Author & Educator) I-04-03 Shared imagination (Dr. Douglas C. Engelbart, 197 Bootstrap) I-05 Privacy & Openness I-05-01 We’re all swimming in media: End-users must be able 201 to keep secrets (Mitch Ratcliffe, BuzzLogic & Tetriad) I-05-02 Working openly (Lion Kimbro, Programmer and 205 Activist) I-06 Integral Approaches & Global Contexts I-06-01 Meta-intelligence for analyses, decisions, policy, and 213 action: The Integral Process for working on complex issues (Sara Nora Ross, Ph.D. ARINA & Integral Review) I-06-02 Collective intelligence: From pyramidal to global 225 (Jean-Francois Noubel, The Transitioner) I-06-03 Cultivating collective intelligence: A core leadership 235 competence in a complex world (George Pór, Fellow at Universiteit van Amsterdam) II LARGE-SCALE COLLABORATION II-01 Altruism, Group IQ, and Adaptation II-01-01 Empowering individuals towards collective online 245 production (Keith Hopper, KeithHopper.com) II-01-02 Who’s smarter: chimps, baboons or bacteria? The 251 power of Group IQ (Howard Bloom, author) II-01-03 A collectively generated model of the world (Marko 261 A. Rodriguez, Los Alamos National Laboratory) II-02 Crowd Wisdom and Cognitive Bias II-02-01 Science of CI: Resources for change (Norman L 265 Johnson, Chief Scientist at Referentia Systems, former LANL) II-02-02 Collectively intelligent systems (Jennifer H. Watkins, 275 Los Alamos National Laboratory) II-02-03 A contrarian view (Jaron Lanier, scholar-in-residence, 279 CET, UC Berkeley & Discover Magazine) II-03 Semantic Structures & The Semantic Web II-03-01 Information Economy Meta Language (Interview with 283 Professor Pierre Lévy, by George Pór) II-03-02 Harnessing the collective intelligence of the World- 293 Wide Web (Nova Spivack, RadarNetworks, Web 3.0) II-03-03 The emergence of a global brain (Francis Heylighen, 305 Free University of Brussels) II-04 Information Networks II-04-01 Networking and mobilizing collective intelligence (G. Parker Rossman, Future of Learning Pioneer) II-04-02 Toward high-performance organizations: A strategic 333 role for Groupware (Douglas C. Engelbart, Bootstrap) II-04-03 Search panacea or ploy: Can collective intelligence 375 improve findability? (Stephen E. Arnold, Arnold IT, Inc.) II-05 Global Games, Local Economies, & WISER II-05-01 World Brain as EarthGame (Robert Steele and many 389 others, Earth Intelligence Network) II-05-02 The Interra Project (Jon Ramer and many others) 399 II-05-03 From corporate responsibility to Backstory 409 Management (Alex Steffen, Executive Editor, Worldchanging.com) II-05-04 World Index of Environmental & Social 413 Responsibility (WISER) By the Natural Capital Institute II-06 Peer-Production & Open Source Hardware II-06-01 The Makers’ Bill of Rights (Jalopy, Torrone, and Hill) 421 II-06-02 3D Printing and open source design (James Duncan, 423 VP of Technology at Marketingisland) II-06-03 REBEARTHTM: 425 II-07 Free Wireless, Open Spectrum, and Peer-to-Peer II-07-01 Montréal Community Wi-Fi (Île Sans Fil) (Interview 433 with Michael Lenczner by Mark Tovey) II-07-02 The power of the peer-to-peer future (Jock Gill, 441 Founder, Penfield Gill Inc.) Growing a world 6.6 billion people would want to live in (Marc Stamos, B-Comm, LL.B) II-07-03 Open spectrum (David Weinberger) II-08 Mass Collaboration & Large-Scale Argumentation II-08-01 Mass collaboration, open source, and social 455 entrepreneurship (Mark Tovey, Advanced Cognitive Engineering Lab, Institute of Cognitive Science, Carleton University) II-08-02 Interview with Thomas Homer-Dixon (Hassan 467 Masum, McLaughlin-Rotman Center for Global Health) II-08-03 Achieving collective intelligence via large-scale argumentation (Mark Klein, MIT Center for Collective Intelligence) II-08-04 Scaling up open problem solving (Hassan Masum & 485 Mark Tovey) D Afterword: The Internet and the revitalization of 495 democracy (The Rt. Honourable Paul Martin & Thomas Homer-Dixon) E Epilogue by Tom Atlee 513 F Three Lists 515 1. Strategic Reading Categories 2. Synopsis of the New Progressives 3. Fifty-Two Questions that Matter G Glossary 519 H Index 52

Proceedings of the European Conference on Agricultural Engineering AgEng2021

This proceedings book results from the AgEng2021 Agricultural Engineering Conference under auspices of the European Society of Agricultural Engineers, held in an online format based on the University of Évora, Portugal, from 4 to 8 July 2021. This book contains the full papers of a selection of abstracts that were the base for the oral presentations and posters presented at the conference. Presentations were distributed in eleven thematic areas: Artificial Intelligence, data processing and management; Automation, robotics and sensor technology; Circular Economy; Education and Rural development; Energy and bioenergy; Integrated and sustainable Farming systems; New application technologies and mechanisation; Post-harvest technologies; Smart farming / Precision agriculture; Soil, land and water engineering; Sustainable production in Farm buildings