To trade effectively and profitably in new electricity market structures, participants need to identify how best to use information available to them. In many cases only incomplete information will be available for short-term planning, trading and decision-making. This paper simulates a group of generators who adapt bidding behaviours in different segments of liberalised electricity markets based on historic market information, observed strategies and their view of other market participants. Results show that even in the incomplete information case efficient bidding strategy for market participants can be identified. Specifically, this paper presents some key findings from an active electricity market and utilises them within an electricity market simulation. The benefit of market simulation for participants is identified and reported
Adjustment of a given age distribution to a desired age distribution within a required time frame is dynamically performed for the purpose of Human Resource (HR) planning in Human Resource Management (HRM). The adjustment process is carried out by adding the adjustment magnitudes to the existing number of employees at the selected age groups on the yearly basis. A model of a discrete dynamical system is employed to emulate the evolution of the age distribution used under the adjustment process. Genetic Algorithms (GA) is applied for determining the adjustment magnitudes that influence the dynamics of the system. An interesting aspect of the problem lies in the high number of constraints; though the constraints are fundamental, they are considerably higher in number than in many other optimization problems. An adaptive penalty scheme is proposed for handling the constraints.Numerical examples show that GA with the utilized adaptive penalty scheme provides potential means for HR planning in HRM.
We propose the conceptual model of incorporative energies and technologies, which they are designed for a smart society that can be established under the use of green energy concept for sustainable living. Basically, the use of natural resource with green environment and sustainability has become the critical issue of the world society, where the sustainable energy resources such as solar cells, wind energy and wave energy have been the promising target requirements. The smart society with green energy suppliers can give the modern society living facilities, where the sustainable life is the advantage. In this paper, the incorporative appliance between green energy and smart society is designed and the conceptual model discussed. This proposed concept can be planned, implemented and realized in the near future.
Abstract:Ideally with no constraints on the budget, an investment in information technology should be easy and straightforward. Conventional method for the IT investment is adapted from the existing financial techniques which focus mainly on the returns from the assets invested. However, due to specific natures of an IT asset, financial techniques may become inappropriate and misleading. This paper proposes an alternative investment framework for the information technology assets by utilising the experiences of experts since its installation. To utilise these experiences in the proposed investment framework, the learning curve is constructed and represents as the organisational learning model in costs, performance and risks according to the asset management framework. College of Arts, Media and Technology within Chiang Mai University is used as the case study. The results have shown that the alternative investment framework performs better than conventional evaluation methods and leads to the most suitable investment option.
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