Mustafa Jahangoshai Rezaee - Department ofIndustrialEngineering.Iran UniversityofScienceand Technology, Tehran, Iran.
Ehram Safari - Department of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran,

Most of the problems in real world are modeling like a multiple objective problems (MOP). The MOPs are usually difficult for solving. Therefore, we must be designed new algorithms and approaches or extend exciting algorithms for solving them. This paper discusses simple and useful integrated approach for reducing the number of objectives in multiple objective problems. For this purpose, principal component analysis (PCA) can be used. The method consists of a two-stage algorithm. In first stage, using PCA for reducing objects. This reducing obtains from two different ways. In second stage, we use results of previous stage for solving problem like a single objective problem. The new objective function covers maximum variances of primitive functions. We show that the proposed method is able to generate efficient solution without extra constraints and variables than the general linear program found in the literature. An example is presented to illustrate the steps of the procedure.

Multi-Objective Problem; Principal Component Analysis; Reduction Objectives