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the term integrated to be associated with tightly coupled linkages that are accomplished by application of standards and development of enterprise application interfaces By contrast, some use the term interoperability to describe linkages Interoperability implies the ability of a system or product to work with other systems or products without special effort on the part of the customer or user Words such as loose coupling, adaptive, and noninvasive are used to differentiate interoperable linkages from integrated linkages These ideas are important in understanding the attributes and characteristics of enterprise performance-improving strategies and solutions They help the people who must plan, budget, and pay for solutions to better understand the trade-offs from the technologies enabling results Technologies affect how work gets done and how results are produced with associated attributes and metrics When there is a surplus of labor or people needing work, some leaders may be more inclined to use people versus technology to perform work When there are shortages, outsourcing and worker immigration are alternatives The sociogeopolitical trade-offs are real for government leaders and for American commercial enterprises alike Metaphors are used to help explain complex ideas Supply chain and value chain are used to describe the relationship among trading partners that comprise an enterprise Chains describe dependent relationships, yet the linkages we are developing with application of new technology may be better described as neurons and synapses (Neurons are nerve cells that can receive and send information by way of synaptic connections) Chains are rigid and hard to break Neurons and synapses work as more agile and adaptable means of linking Those performing enterprise integration need to adopt a different view from systems integration To illustrate this, compare systems integration to that of a castle and enterprise integration to that of the open marketplace There is only one way into the castle and that is to take the bridge over the mote that is opened and closed by request to the gatekeeper By contrast, the open market may be accessed by anyone entering from all sides The difference is context A commercial enterprise participating in the government market must cross many motes and gatekeepers, though the goal is to make the enterprise more open like the marketplace Systems integration is more concerned about performance inside organizational or functional boundaries that are often called silos Enterprise integration must consider how software solutions perform for all of the entities that share information As much value is given to how systems perform in the enterprise context as is given to the local context A more advanced topic has to do with consideration of self-organization versus entropy and striking a balance between freedom and constraints From the viewpoint of a supplier or subcontractor that is a member of the larger enterprise, and from the viewpoint of prime contractors and ultimate customers, achieving the optimum degree of freedom while ensuring enterprise-wide interoperability is a goal.

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The main swarm uses a cognition-only model (refer to Section 1635) to promote exploration of the search space Because the social component serves as an attractor for all particles, it is removed from the velocity update equation This allows particles to converge on di erent parts of the search space It is important to note that velocities must be initialized to zero Sub-swarm Training The sub-swarms are independent swarms, trained using a full model PSO (refer to Section 161) Using a full model to train sub-swarms allows particle positions to be adjusted on the basis both of particle s own experience (the cognitive component) and of socially obtained information (the social component) While any full model PSO can be used to train the sub-swarms, the NichePSO as presented in [88, 89] uses the GCPSO (discussed in Section 1651) The GCPSO is used since it has guaranteed convergence to a local minimum [863], and because the GCPSO has been shown to perform well on extremely small swarms [863] The latter property of GCPSO is necessary because sub-swarms initially consist of only two particles The gbest PSO has a tendency to stagnate with such small swarms Identification of Niches A sub-swarm is formed when a particle seems to have converged on a solution If a particle s tness shows little change over a number of iterations, a sub-swarm is created with that particle and its closest topological neighbor Formally, the standard deviation, i , in the tness f (xi ) of each particle is tracked over a number of iterations If i < , a sub-swarm is created To avoid problem-dependence, i is normalized according to the domain The closest neighbor, l, to the position xi of particle i is computed using Euclidean distance, ie l = arg min{||xi xa ||}

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(1698)

with 1 i, a Sns , i = a and Sns is the size of the main swarm The sub-swarm creation, or niche identi cation process is summarized in Algorithm 1616 In this algorithm, Q represents the set of sub-swarms, Q = {S1 , , SK }, with |Q| = K Each sub-swarm has Sk ns particles During initialization of the NichePSO, K is initialized to zero, and Q is initialized to the empty set Absorption of Particles into a Sub-swarm It is likely that particles of the main swarm move into the area of the search space covered by a sub-swarm Sk Such particles are merged with the sub-swarm, for the following reasons:

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