A plan is a sequence of actions which when executed will achieve some pre-set goal or goals, and by planning we mean the creation of such plans. It is in order to achieve the automation of the planning process that Ar...
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A plan is a sequence of actions which when executed will achieve some pre-set goal or goals, and by planning we mean the creation of such plans. It is in order to achieve the automation of the planning process that Artificial Intelligence (AI) planning research was begun. An internal research and development project carried out by Scicon Ltd has studied AI planning techniques and produced a software demonstrator system, Scinapse, for the purpose of investigating the feasibility of this approach to real applications. Scinapse has been applied to a logistics problem involving the planning of land and sea transport movements. The logistics application was chosen as an example for various reasons, not least the ability of non-experts in the fields of AI planning and logistics to readily understand the problem and to see how solutions are reached.
Techniques such as CPA and PERT have become a pre-requisite for the successful management of large-scale projects. However, these techniques form the basis for advanced concepts and potential tools, to assist with spe...
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Techniques such as CPA and PERT have become a pre-requisite for the successful management of large-scale projects. However, these techniques form the basis for advanced concepts and potential tools, to assist with specific problems routinely encountered by project managers. An example is the problem of project expedition. Here, the aim is to reduce the duration of a project in order to meet a specified target date, by the identification of particular activities within the project to which additional resources must be applied. Such expedition will inevitably incur an increase in expenditure. Therefore careful attention must be paid to the selection process that provides a least-cost plan. However, current solutions have many drawbacks ranging from lack of computer implementation, to the burdensome overhead in obtaining the data, and consequently are rarely used. In this paper a systems approach was adopted to counter the shortfalls indicated above.
The quest for a practical method for the design of controllers for interactive multivariable processes has thrown up an array of design methodologies. It has been stated in numerous publications that a wide chasm has ...
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The quest for a practical method for the design of controllers for interactive multivariable processes has thrown up an array of design methodologies. It has been stated in numerous publications that a wide chasm has developed between the theory of control and its application. However, closer inspection indicates that the majority of today's approaches to multivariable control rely heavily on unrealistically accurate plant models and are both difficult and unwieldy to use on systems with more than three inputs and three outputs. In view of the success of the Ziegler and Nichols tuning rules for single-input single-output plants, research effort has been directed at producing a multivariable counterpart to this monovariable method. The recently developed multivariable design methods for PI and PID multivariable controllers deal with fixed-parameter plants and non-linear plants, and are best regarded as the extension to multivariable plants of the highly successful technique of Ziegler and Nichols.
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