ITSM Strategy Using CSI on ITIL V.3 To Improve IT Services

The SIMBARU (Academic information System) has The obstacles that currently occur in the SIMBARU process is how to utilize an IT-based academic service system that is ready to run/use in the optimal time optimally, providing services with the right target, fast access that can provide satisfaction to users (user), as well as vision of mission and institutional business objectives can be realized. By using PDCA data analysis Method (Plan, Do, Check, and ACT), it is expected to design a SIP document (Service Improvement Plan) to improve the performance of SIMBARU. The design of SIP documents on SIMBARU can be done by using IT Infrastructure Library V. 3 by analyzing the condition of SIMBARU which then produce output in the form of SIP. Results of this research SIP designed in accordance with the knowledge gained from the results of the analysis, can be used as a strategy to improve IT services in college, which resulted in recommendation of improvement and output in the form of SIP. Repair and SIP recommendations are expected to be implemented to improve IT services, so that the IT service i.e. SIMBARU can help the academic staff in conducting academics in college.The SIMBARU (Academic information System) has The obstacles that currently occur in the SIMBARU process is how to utilize an IT-based academic service system that is ready to run/use in the optimal time optimally, providing services with the right target, fast access that can provide satisfaction to users (user), as well as vision of mission and institutional business objectives can be realized. By using PDCA data analysis Method (Plan, Do, Check, and ACT), it is expected to design a SIP document (Service Improvement Plan) to improve the performance of SIMBARU. The design of SIP documents on SIMBARU can be done by using IT Infrastructure Library V. 3 by analyzing the condition of SIMBARU which then produce output in the form of SIP. Results of this research SIP designed in accordance with the knowledge gained from the results of the analysis, can be used as a strategy to improve IT services in college, which resulted in recommendation of improvement and output in the form of SIP. Repair and SIP recommendations are expected to be implemented to improve IT services, so that the IT service i.e. SIMBARU can help the academic staff in conducting academics in college

A Domain-Independent Algorithm for Plan Adaptation

The paradigms of transformational planning, case-based planning, and plan debugging all involve a process known as plan adaptation - modifying or repairing an old plan so it solves a new problem. In this paper we provide a domain-independent algorithm for plan adaptation, demonstrate that it is sound, complete, and systematic, and compare it to other adaptation algorithms in the literature. Our approach is based on a view of planning as searching a graph of partial plans. Generative planning starts at the graph's root and moves from node to node using plan-refinement operators. In planning by adaptation, a library plan - an arbitrary node in the plan graph - is the starting point for the search, and the plan-adaptation algorithm can apply both the same refinement operators available to a generative planner and can also retract constraints and steps from the plan. Our algorithm's completeness ensures that the adaptation algorithm will eventually search the entire graph and its systematicity ensures that it will do so without redundantly searching any parts of the graph.Comment: See http://www.jair.org/ for any accompanying file

A reusable iterative optimization software library to solve combinatorial problems with approximate reasoning

Real world combinatorial optimization problems such as scheduling are typically too complex to solve with exact methods. Additionally, the problems often have to observe vaguely specified constraints of different importance, the available data may be uncertain, and compromises between antagonistic criteria may be necessary. We present a combination of approximate reasoning based constraints and iterative optimization based heuristics that help to model and solve such problems in a framework of C++ software libraries called StarFLIP++. While initially developed to schedule continuous caster units in steel plants, we present in this paper results from reusing the library components in a shift scheduling system for the workforce of an industrial production plant.Comment: 33 pages, 9 figures; for a project overview see http://www.dbai.tuwien.ac.at/proj/StarFLIP

Identifying and Exploiting Features for Effective Plan Retrieval in Case-Based Planning

Case-Based planning can fruitfully exploit knowledge gained by solving a large number of problems, storing the corresponding solutions in a plan library and reusing them for solving similar planning problems in the future. Case-based planning is extremely effective when similar reuse candidates can be efficiently chosen. In this paper, we study an innovative technique based on planning problem features for efficiently retrieving solved planning problems (and relative plans) from large plan libraries. A problem feature is a characteristic of the instance that can be automatically derived from the problem specification, domain and search space analyses, and different problem encodings. Since the use of existing planning features are not always able to effectively distinguish between problems within the same planning domain, we introduce a new class of features. An experimental analysis in this paper shows that our features-based retrieval approach can significantly improve the performance of a state-of-the-art case-based planning system