A Multiobjective Optimization Model for Packing Proposals in Large-Scale R&D Project Review

Author

Yuan, Chen ; Zhi-ping, Fan

Author_Institution

Sch. of Bus. Adm., Northeastern Univ.

fYear

2006

fDate

5-7 Oct. 2006

Firstpage

359

Lastpage

363

Abstract

To solve the packing proposals problem in large-scale R&D project review, a-nonlinear 0-1 integer programming model with multiobjective is presented. The first objective is to minimize the quantity difference between the number of proposals for each package and the average number of proposals that peer reviewers would like to review. The second objective is to minimize the probability that proposals belong to the same organization be packed into one package. A weighted sum method is applied to treat multiple objectives. Then, a genetic algorithm with sequence encoding and PMX crossover is developed to solve this model. Finally, a numerical experiment designed to simulate the proposal packing process of NSFC is described to illustrate the use of the proposed method

Keywords

bin packing; genetic algorithms; integer programming; nonlinear programming; probability; genetic algorithm; integer programming model; large-scale R&D project; multiobjective optimization model; nonlinear programming; packing proposal problem; probability; Design optimization; Encoding; Genetic algorithms; Large-scale systems; Linear programming; Mathematical model; Optimization methods; Packaging; Proposals; Research and development; Genetic algorithm; Multiobjective optimization; Packing proposals; R&D project review;

fLanguage

English

Publisher

ieee

Conference_Titel

Management Science and Engineering, 2006. ICMSE '06. 2006 International Conference on

Conference_Location

Lille

Print_ISBN

7-5603-2355-3

Type

conf

DOI

10.1109/ICMSE.2006.313841

Filename

4104924