The Budgeted Transportation Problem

TL;DR

This paper introduces an auction-based primal-dual approximation algorithm for the Budgeted Transportation Problem, optimizing profit under source capacities and sink budgets, and extends it to more general cases with edge capacities and concave profit functions.

Contribution

It proposes a novel approximation algorithm for the Budgeted Transportation Problem and generalizes it to handle additional constraints and profit functions.

Findings

Algorithm achieves complexity $O(rac{1}{\epsilon}(n^2 + n \log m)m \log U)$

Extension to problems with edge capacities and concave profit functions

Provides a scalable approximation approach for complex transportation problems

Abstract

Consider a transportation problem with sets of sources and sinks. There are profits and prices on the edges. The goal is to maximize the profit while meeting the following constraints; the total flow going out of a source must not exceed its capacity and the total price of the incoming flow on a sink must not exceed its budget. This problem is closely related to the generalized flow problem. We propose an auction based primal dual approximation algorithm to solve the problem. The complexity is $O(\epsilon^{-1}(n^2+ n\log{m})m\log U)$ where $n$ is the number of sources, $m$ is the number of sinks, $U$ is the ratio of the maximum profit/price to the minimum profit/price. We also show how to generalize the scheme to solve a more general version of the problem, where there are edge capacities and/or the profit function is concave and piece-wise linear. The complexity of the algorithm depends on the number of linear segments, termed ${\cal L}$, of the profit function.