“A framework for co-optimization algorithm performance and its application to worst-case optimization”, Theoretical Computer Science (2014) How do you implement an optimal algorithm to search for solutions (e.g. business policies, engineering designs) that are good across many different circumstances? … to read more click here. |
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“Predicting the Unpredictable”, Harvard Business Review The collective behavior of people in crowds, markets, and organizations can easily elude any top-down analysis…to read more, click here to download. |
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“Don’t Trust Your Gut”, Harvard Business Review How do you analyze more in less time? Powerful new decision-support tools can help executives quickly sort through vast numbers of alternatives and pick the best ones…to read more, click here to download. |
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“Agent-Based Modeling: Methods and Techniques for Simulating Human Systems”, Proc. National Academy of Science The basic principles of agent-based simulation are briefly introduced along with its four areas of application are discussed by using real-world applications. For each category, one or several business applications are described and analyzed…to read more, click here to download. |
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“Swarm Intelligence: A Whole New Way to Think About Business”, Harvard Business Review Research into the behavior of social insects has helped several companies, including Unilever, McGraw-Hill, and Capital One, to develop more efficient ways to schedule factory equipment, divide tasks among workers, organize people, and even plot strategy… click here to read the full article on HBR. |
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“A More Rational Approach to New Product Development”, Harvard Business Review The Chorus model delivers new molecules at almost twice the speed and less than a third of the cost of the standard process…to read more, click here to download. |
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“Understanding and Managing Complexity Risk”, MIT Sloan Management Review Increased complexity of a company’s systems – products, processes, technologies, organizational structures, legal contracts and so on – can create vulnerabilities. Three complimentary strategies can help mitigate the risk…to read more, click here to download. |
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“Decisions 2.0: The Power of Collective Intelligence”, MIT Sloan Management Review Information markets, wikis and other applications that tap into the collective intelligence of groups have recently generated tremendous interest. But what’s the reality behind the hype?…to read more, click here to download. |
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“Swarm Smarts”, American Scientist Using ants and other social insects as models, computer scientists have created software agents that cooperate to solve complex problems, such as the rerouting of traffic in a busy telecom network…to read more, click here to download. |
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“Interactive Multi-Participant Tour Allocation”, Evolutionary Computation An evolutionary technique originally developed to generate “interesting” images and pieces of art can be used to perform task allocation by integrating subjective criteria and subjective knowledge into the search process…to read more, click here to download. |
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“Scale-Free Networks”, Scientific American Many networks–from the World Wide Web to a cell’s metabolic system to actors in Hollywood–are dominated by important nodes, or hubs, that have a seemingly unlimited number of links. These networks are remarkably resistant to accidental failures but extremely vulnerable to coordinated attacks…to read more, click here to download. |
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“The Effects of Word-of-Mouth: An Agent-Based Simulation of Interpersonal Influence in Social Networks”, Word of Mouth Research Symposium There has been a growing interest among social scientists – and particularly the marketing community – in the notion of influentials, individuals who have a disproportionate influence on the spread of information and in the formation of opinions in their society…to read more, click here to download. |
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“An Agent-Based Modeling Approach for Studying Manpower and Personnel Management Behaviors”, Proceedings of the 2007 Winter Simulation Conference A computer simulation is described which illustrates how stress and motivation influence a sailor’s performance and his or her decision to reenlist or to leave the US Navy. An agent-based model of the US Navy’s Manpower and Personnel (M&P) systems is used to simulate shipboard behavior and includes the determination of manpower requirements, the budget allocation for fulfilling these requirements (manpower programming), the provision of people to fulfill the requirements (personnel planning),and the distribution of the available personnel…to read more, click here to download. |
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