By Efraim; Liang, Ting-Peng; Aronson, Jay E. Turban
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Additional resources for Decision Support Systems and Intelligent Systems 7th
13 ADVANCED INTELLIGENT DECISION SUPPORT SYSTEMS At the cutting edge of applied artificial intelligence are several exciting technologies that assist decision-makers. These include genetic algorithms, fuzzy logic, and intelligent agents (IA). Genetic algorithms solve problems in an evolutionary way. They mimic the process of evolution and search for an extremely good solution. Survival of the fittest guides this method. Genetic algorithms have been used to maximize advertising profit at tele- CHAPTER 1 MANAGEMENT SUPPORT SYSTEMS: AN OVERVIEW 25 EXPERT SYSTEMS PROVIDE USEFUL ADVICE Suppose you manage an engineering firm that bids on many projects.
It can handle the imprecise nature of how humans communicate information. " on a hot day. Consider how hot is hot? Would one degree cooler still be really hot, or simply hot? This imprecision can be handled mathematically in a precise way to assist decision-makers in solving problems with imprecise statements of their parameters. Usually fuzzy logic methods are combined with other artificial intelligence methods, such as expert systems and artificial neural networks, to boost their accuracy in their decision-making.
With computers, decision-makers can perform complex simulations, check many possible scenarios, and assess diverse impacts quickly and economically (see Saltzman and Mehrotra, 2001). All these capabilities lead to better decisions. Competitive edge: enterprise resource management and empowerment. Competitive pressures make the job of decision-making difficult. Competition is based not just on price but on quality, timeliness, customization of products, and customer support. Organizations must be able to frequently and rapidly change their mode of operation, reengineer processes and structures, empower employees, and innovate.