Application of Objective-Space and Multi-Objective Plant Propagation Algorithms to Multi-Objective Linear Programming

Abstract

The solution of Multiple Objective Linear Programming (MOLP) problem is usually obtained by exact methods. However, nature-inspired population-based algorithms such as the multi-objective plant propagation algorithm (MOPPA) is becoming more and more prominent. This paper presents an application of the multiple-objective plant propagation algorithm (MOPPA) and an Objective space-based method known as Benson’s outer approximation algorithm to multi-objective linear programming in order to compare the quality of nondominated points returned by these two Algorithms. Computational results for a selected group of 20 MOLP instances ranging from small to realistic instances was reported. It was observed that Benson’s outer approximation algorithm is superior to MOPPA in terms of the quality of nondominated points it returned.