Random problem genertion and the computation of efficient extreme points in multiple objective linear programming. This paper looks at the task of computing efficient extreme points in multiple objective linear programming. Vector maximization software is reviewed and the ADBASE solver for computing all efficient extreme points of a multiple objective linear program is described. To create MOLP test problems, models for random problem generation are discussed. In the computational part of the paper, the numbers of efficient extreme points possessed by MOLPs (including multiple objective transportation problems) of different sizes are reported. In addition, the way the utility values of the efficient extreme points might be distributed over the efficient set for different types of utility functions is investigated. Not surprisingly, results show that it should be easier to find good near- optimal solutions with linear utility functions than with, for instance, Tchebycheff types of utility functions.
Keywords for this software
References in zbMATH (referenced in 64 articles )
Showing results 61 to 64 of 64.
- Nykowski, I.; Zolkiewski, Z.: A compromise procedure for the multiple objective linear fractional programming problem (1985)
- Rakes, Terry R.; Reeves, Gary R.: Selecting tolerances in chance-constrained programming: A multiple objective linear programming approach (1985)
- Steuer, Ralph E.: Operating considerations pertaining to the interactive weighted Tchebycheff procedure (1984)
- Steuer, Ralph E.; Choo, Eng-Ung: An interactive weighted Tchebycheff procedure for multiple objective programming (1983)