Senior Lecturer, CS / IT Dept. JIITU, Noida. firstname.lastname@example.org Phone No.:09810490704 a b
Student, CS / IT Dept JIITU, Noida email@example.com Phone No.: 09871277845
Student, CS / IT Dept JIITU, Noida firstname.lastname@example.org Phone No:09911867266 c
ABSTRACT Decision support systems combine individuals' and computers' capabilities to improve the quality of decisions. We have tried to add value to the decision making software by enabling them provide efficient solution through incorporation of Dynamic Programming Techniques. We have integrated various decision support tools e.g. Data warehousing, Data mining, and Dynamic Programming approach to arrive at an actionable solution.
2. Review Present Decision support systems are a cohesive, integrated system of hardware and software designed specifically to manipulate data and enable users to support problem solving and decision making by drawing useful information from disparate sources of data with the help of mining techniques. While data mining can assist in the automated discovery of actionable  insights from data, the efficient execution of the actions can only be effected by coupling the output of data mining with mathematical optimization methods. Very often the actionable insights need to be acted upon taking into account business constraints such as budgets and schedules. In this paper, effort is to take the decision support systems up one level. We have tried to discover unknown information by predictive analysis of data. Based on the predicted results, with the help of Dynamic Programming techniques we attempt to find out efficient solution scenario which makes decision making both Dynamic and much more effective. One major role that technology plays is supporting analysis. Yet another technology capability, which is in increasing demand, is to recommend specific actions based on the optimization of mathematical models of the decision problem applied to identify the best action to take. The idea can be better illustrated with the help of following figure:
Decision support system, High-end Decision making, Data mining, Data warehousing, Dynamic programming, Revenue optimization. 1. Introduction Decision-making in management has always involved utilization of different information assets. Contemporary organizations are not concerned because of lack of information but information overload and information dispersion. The second main concern is when in an industry the perishability and the variability of the product is very high both in demand and the supply side, then it becomes very vulnerable. In these industries Decision making is very critical because the demand is never same; it heavily fluctuates depending on numerous facts. More than decision support it’s important that target audience for the business intelligence software is provided with immediate response according to different conditions and corresponding behavior of customers so that decision making becomes more convenient and rather meaningful.
Mining over data for extraction of actionable information. Applying Dynamic programming techniques to attain optimal solution.
These are discussed in detail about how to approach towards each step. At every step demonstration of suitable techniques are given to exhibit a prospective view of decision making application software which will enables user with high end decision making. 3.1 Identification of business problems Successfully supporting managerial decisionmaking is critically dependent upon the availability of integrated, high quality information organized and presented in a timely and easily understood manner. For development of a profit maximizing decision making system, modeling of data is inevitable because yield management system in the multiplex business is comprised of various aspects like...