Finding Decision Rules with Genetic Algorithms

نویسنده

  • E. Johnson
چکیده

Many decisions involve conflicting objectives that cannot be optimized simultaneously. For example, in choosing an apartment, none of the available options typically has the best commute, is in the nicest neighborhood, and rents for the lowest price; in making a decision of this sort, we examine tradeoffs. How these tradeoffs are made depends on the decision process and preferences of the decision maker.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

FINDING HIGHLY PROBABLE DIFFERENTIAL CHARACTERISTICS OF SUBSTITUTION-PERMUTATION NETWORKS USING GENETIC ALGORITHMS

In this paper, we propose a genetic algorithm, called GenSPN, for finding highly probable differential characteristics of substitution permutation networks (SPNs). A special fitness function and a heuristic mutation operator have been used to improve the overall performance of the algorithm. We report our results of applying GenSPN for finding highly probable differential characteristics of Ser...

متن کامل

A Set of Algorithms for Solving the Generalized Tardiness Flowshop Problems

This paper considers the problem of scheduling n jobs in the generalized tardiness flow shop problem with m machines. Seven algorithms are developed for finding a schedule with minimum total tardiness of jobs in the generalized flow shop problem. Two simple rules, the shortest processing time (SPT), and the earliest due date (EDD) sequencing rules, are modified and employed as the core of seque...

متن کامل

Yarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms

Yarn tenacity is one of the most important properties in yarn production. This paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. The artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 Ne. As the first step for modeling, the empirical data is col...

متن کامل

Finding the Optimal Path to Restoration Loads of Power Distribution Network by Hybrid GA-BCO Algorithms Under Fault and Fuzzy Objective Functions with Load Variations

In this paper proposes a fuzzy multi-objective hybrid Genetic and Bee colony optimization algorithm(GA-BCO) to find the optimal restoration of loads of power distribution network under fault.Restoration of distribution systems is a complex combinatorial optimization problem that should beefficiently restored in reasonable time. To improve the efficiency of restoration and facilitate theactivity...

متن کامل

Finding Small High Performance Subsets of Induced Rule Sets: Extended Summary

Models consisting of decision rules – such as those produced by methods from Pawlak’s rough set theory – generally have a white-box nature, but in practice induced models are too large to be inspected. Here, we investigate methods for simplifying complex models while retaining predictive performance. The approach taken is rule filtering, i.e. post-pruning of complete rules. Two methods for find...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005