Incorporation of Preferences in an Evolutionary Algorithm Using an Outranking Relation: The EvABOR Approach

نویسندگان

  • Eunice Oliveira
  • Carlos Henggeler Antunes
  • Álvaro Gomes
چکیده

The incorporation of preferences into Evolutionary Algorithms (EA) presents some relevant advantages, namely to deal with complex real-world problems. It enables focus on the search thus avoiding the computation of irrelevant solutions from the point of view of the practical exploitation of results (thus minimizing the computational effort), and it facilitates the integration of the DM’s expertise into the solution search process (thus minimizing the cognitive effort). These issues are particularly important whenever the number of conflicting objective functions and/or the number of non-dominated solutions in the population is large. In EvABOR (Evolutionary Algorithm Based on an Outranking Relation) approaches preferences are elicited from a decision maker (DM) with the aim of guiding the evolutionary process to the regions of the space more in accordance with the DM’s preferences. The preferences are captured and made operational by using the technical parameters of the ELECTRE TRI method. This approach is presented and analyzed using some illustrative results of a case study of electrical networks. Eunice Oliveira Polytechnic Institute of Leiria, Portugal & R&D Unit INESC Coimbra, Portugal Carlos Henggeler Antunes University of Coimbra, Portugal & R&D Unit INESC Coimbra, Portugal Álvaro Gomes University of Coimbra, Portugal & R&D Unit INESC Coimbra, Portugal DOI: 10.4018/978-1-4666-4253-9.ch004

برای دانلود 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

A Multiobjective Evolutionary Algorithm for Deriving Final Ranking from a Fuzzy Outranking Relation

The multiple criteria aggregation methods allow us to construct a recommendation from a set of alternatives based on the preferences of a decision maker. In some approaches, the recommendation is immediately deduced from the preferences aggregation process. When the aggregation model of preferences is based on the outranking approach, a special treatment is required, but some non-rational viola...

متن کامل

A comparative study of different approaches using an outranking relation in a multi-objective evolutionary algorithm

This paper presents a comparative analysis of three versions of an evolutionary algorithm in which the decision maker’s preferences are incorporated using an outranking relation and preference parameters associated with the ELECTRE TRI method. The aim is using the preference information supplied by the decision maker to guide the search process to the regions where solutions more in accordance ...

متن کامل

Multi-layer Clustering Topology Design in Densely Deployed Wireless Sensor Network using Evolutionary Algorithms

Due to the resource constraint and dynamic parameters, reducing energy consumption became the most important issues of wireless sensor networks topology design. All proposed hierarchy methods cluster a WSN in different cluster layers in one step of evolutionary algorithm usage with complicated parameters which may lead to reducing efficiency and performance. In fact, in WSNs topology, increasin...

متن کامل

Evolutionary User Clustering Based on Time-Aware Interest Changes in the Recommender System

The plenty of data on the Internet has created problems for users and has caused confusion in finding the proper information. Also, users' tastes and preferences change over time. Recommender systems can help users find useful information. Due to changing interests, systems must be able to evolve. In order to solve this problem, users are clustered that determine the most desirable users, it pa...

متن کامل

A Hierarchy Topology Design Using a Hybrid Evolutionary Algorithm in Wireless Sensor Networks

Wireless sensor network a powerful network contains many wireless sensors with limited power resource, data processing, and transmission abilities. Wireless sensor capabilities including computational capacity, radio power, and memory capabilities are much limited. Moreover, to design a hierarchy topology, in addition to energy optimization, find an optimum clusters number and best location of ...

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

برای دانلود 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

عنوان ژورنال:
  • IJNCR

دوره 2  شماره 

صفحات  -

تاریخ انتشار 2011