Adaptive particle swarm optimization

An adaptive particle swarm optimization (APSO) that features better search efficiency than classical particle swarm optimization (PSO) is presented. More importantly, it can perform a global search over the entire search space with faster convergence speed. The APSO consists of two main steps. First, by evaluating the population distribution and particle fitness, a real-time evolutionary state estimation procedure is performed to identify one of the following four defined evolutionary states, including exploration, exploitation, convergence, and jumping out in each generation. It enables the automatic control of inertia weight, acceleration coefficients, and other algorithmic parameters at run time to improve the search efficiency and convergence speed. Then, an elitist learning strategy is performed when the evolutionary state is classified as convergence state. The strategy will act on the globally best particle to jump out of the likely local optima. The APSO has comprehensively been evaluated on 12 unimodal and multimodal benchmark functions. The effects of parameter adaptation and elitist learning will be studied. Results show that APSO substantially enhances the performance of the PSO paradigm in terms of convergence speed, global optimality, solution accuracy, and algorithm reliability. As APSO introduces two new parameters to the PSO paradigm only, it does not introduce an additional design or implementation complexity

Cloud computing resource scheduling and a survey of its evolutionary approaches

A disruptive technology fundamentally transforming the way that computing services are delivered, cloud computing offers information and communication technology users a new dimension of convenience of resources, as services via the Internet. Because cloud provides a finite pool of virtualized on-demand resources, optimally scheduling them has become an essential and rewarding topic, where a trend of using Evolutionary Computation (EC) algorithms is emerging rapidly. Through analyzing the cloud computing architecture, this survey first presents taxonomy at two levels of scheduling cloud resources. It then paints a landscape of the scheduling problem and solutions. According to the taxonomy, a comprehensive survey of state-of-the-art approaches is presented systematically. Looking forward, challenges and potential future research directions are investigated and invited, including real-time scheduling, adaptive dynamic scheduling, large-scale scheduling, multiobjective scheduling, and distributed and parallel scheduling. At the dawn of Industry 4.0, cloud computing scheduling for cyber-physical integration with the presence of big data is also discussed. Research in this area is only in its infancy, but with the rapid fusion of information and data technology, more exciting and agenda-setting topics are likely to emerge on the horizon

Genetic learning particle swarm optimization

Social learning in particle swarm optimization (PSO) helps collective efficiency, whereas individual reproduction in genetic algorithm (GA) facilitates global effectiveness. This observation recently leads to hybridizing PSO with GA for performance enhancement. However, existing work uses a mechanistic parallel superposition and research has shown that construction of superior exemplars in PSO is more effective. Hence, this paper first develops a new framework so as to organically hybridize PSO with another optimization technique for “learning.” This leads to a generalized “learning PSO” paradigm, the *L-PSO. The paradigm is composed of two cascading layers, the first for exemplar generation and the second for particle updates as per a normal PSO algorithm. Using genetic evolution to breed promising exemplars for PSO, a specific novel *L-PSO algorithm is proposed in the paper, termed genetic learning PSO (GL-PSO). In particular, genetic operators are used to generate exemplars from which particles learn and, in turn, historical search information of particles provides guidance to the evolution of the exemplars. By performing crossover, mutation, and selection on the historical information of particles, the constructed exemplars are not only well diversified, but also high qualified. Under such guidance, the global search ability and search efficiency of PSO are both enhanced. The proposed GL-PSO is tested on 42 benchmark functions widely adopted in the literature. Experimental results verify the effectiveness, efficiency, robustness, and scalability of the GL-PSO

Financing Health Care in Poor Rural Counties in China: Experience from a Township-Based Co-Operative Medical Scheme

The economic reform programme in China, which started in the late 1970s, has had a major impact on rural health services. The replacement of collective agricultural production by the ‘household responsibility system’, lead to the widespread collapse of collective-funded Co-operative Medical Schemes ( CMSs), which at that time assisted farming households with health care costs in more than 90% of villages in rural China. The design and implementation of new forms of CMS which are compatible with the economic reform has become a central focus of rural health policy. With strong political support from the central government, which has proposed that most rural areas should have such schemes in place by 2000, widespread CMS implementation is proceeding at considerable speed. Effective regulation, based on systematic monitoring and evaluation methodologies will be essential if these new schemes are to be sustainable. This paper examines the issues involved using empirical evidence from an evaluation based on the logical framework approach of an experimental scheme which was initiated in Hechi Prefecture, Guangxi Province in 1995. The study findings suggest that the very restricted forms of CMS now being introduced on a widespread basis to meet government targets may have some merit in terms of the organisation and regulation of health services and could represent a valuable first step towards a viable financing option. However, the focus on village based schemes, with minimal levels of funding and consequent inability to provide assistance with drug costs or treatment at higher level facilities, raises considerable doubts as to their sustainability when the current enthusiastic support provided by local government declines. The case study reinforces the point that the establishment of a CMS can do little to overcome basic deficiencies in service provision. It also indicates that such schemes will not solve the problem of access for the poorest households in the absence of specific and effective mechanisms to finance their inclusion

The InterMesh Network Architecture

The rapid spread of mobile devices, the emergence of key wireless technologies, and the nomadic user and computing lifestyles on current networks are continuously evolving in synergy. MANETs, WSNs, and WMNs are examples of self-organizing unstructured networks that have their local communication paradigms and are optimized to perform under their particular physical constraints. Wireless Mesh Networks (WMNs) are particularly interesting because of their ability to operate in a pure ad-hoc mode or to include some infrastructural components, making them suitable for a multitude of applications. Inter-networking among the heterogeneous access networks is currently offered by the Internet Protocol (IP). However, the evolution of and the innovation within these networks is greatly hindered by the rigidity of the current Internet implementation and its lag in efficiently supporting flexible unstructured communication paradigms. To broaden the user\u27s innovation space and to efficiently embrace the characteristics of emerging networks, clean-slate architectural approaches are being pursued. In this paper, we propose InterMesh, a novel iner-networking platform for wireless mesh networks. InterMesh enables heterogeneous access networks to converge at novel Persistent Identification and Networking Layer (PINL), providing a seamless service to individual network entities. This paper identifies the key concepts behind the InterMesh network platform, presents an interesting prototype implementation that can coexist with today\u27s Internet while still be able to evolve separately, and discusses some preliminary performance results of the prototype