Abstract
This paper deals with the impact of transportation problem’s (TP) unbalance on difference between the initial and optimal solution. An analysis based on the executed numerical experiments roughly reveals how the unbalance of linear TP affects differences between objective function values of initial feasible solutions generated by most commonly applied approaches (such as least cost method and Vogel’s approximation method) and optimal solutions. Furthermore, this research addresses the question whether the form and/or the number of decision variables has an influence on such differences. The obtained results have indicated scattered, but roughly visible linear relation between unbalance of linear TP and difference between objective function values of initial and optimal solutions.
Highlights
This paper deals with the impact of transportation problem’s (TP) unbalance on difference between the initial and optimal solution
An analysis based on the executed numerical experiments roughly reveals how the unbalance of linear TP affects differences between objective function values of initial feasible solutions generated by most commonly applied approaches and optimal solutions
In its basic formulation, the total supply is equal to the total demand, in literature known as the balanced TP (BTP)
Summary
This paper deals with the impact of transportation problem’s (TP) unbalance on difference between the initial and optimal solution. The aforesaid equality often does not hold in real-life situations At this point, the unbalanced TPs (UBTP) are found in cases where: i) the supply of good is larger than demand, which is considered as a simpler type of UBTP and solvable by modifying the original problem into a BTP; or ii) where the demand exceeds the supply. The unbalanced TPs (UBTP) are found in cases where: i) the supply of good is larger than demand, which is considered as a simpler type of UBTP and solvable by modifying the original problem into a BTP; or ii) where the demand exceeds the supply In dealing with both types of TPs, researchers were mainly focused on mathematical improvements of solving methods for gaining initial solutions and comparing them where Z denotes the total transportation costs while ci,j and xi,j represent cost parameters and transporting flows from suppliers i to demanders j contained in the criterion of optimization
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