An overview of weighted goal programming: a multi-objective transportation problem with some fresh viewpoints

Goal programming (GP) is one of the widely used and effective method of solving real-world multi-objective decision-making problems. The term multi-objective transportation problem (MOTP) covers a specific class of vector maximum (minimum) linear programming problem that typically has multiple, competing, and incompatible objective functions. In this article, GP and weighted goal programming (WGP) are summarized in MOTP. Furthermore, its advantages over GP are illustrated by a theorem. Additionally, by utilizing WGP, a solution procedure is articulated for MOTP. Finally, an application on screen-panels of mobile devices is presented to explore the applicability. The paper ends with a conclusion and including an outlook to future studies, whereby we address internal and external transportation, and view the internal one with a broader understanding of logistics.

Automated summary

Goal programming is an effective method for solving real-world multi-objective decision-making problems. The term multi-objective transportation problem refers to a specific class of linear programming problems with multiple competing and incompatible objective functions. This article summarizes the application of goal programming and weighted goal programming in multi-objective transportation problems, and illustrates the advantages of the latter through a theorem. A solution procedure for the problem is articulated using weighted goal programming. An application example on screen-panels of mobile devices is presented to demonstrate its applicability. The article concludes with an outlook to future studies, addressing both internal and external transportation and emphasizing a broad understanding of logistics.