Improved Approximation Algorithms for Inventory Problems

TL;DR

This paper introduces improved approximation algorithms for inventory problems, achieving an exponentially better approximation factor of O(log log min(N,T)) using an iterative rounding approach, advancing the state of the art.

Contribution

The paper presents new approximation algorithms for the submodular joint replenishment and inventory routing problems with significantly improved approximation factors.

Findings

Achieved an O(log log min(N,T)) approximation factor.

Applied iterative rounding techniques to inventory problems.

Significantly improved previous approximation bounds.

Abstract

We give new approximation algorithms for the submodular joint replenishment problem and the inventory routing problem, using an iterative rounding approach. In both problems, we are given a set of $N$ items and a discrete time horizon of $T$ days in which given demands for the items must be satisfied. Ordering a set of items incurs a cost according to a set function, with properties depending on the problem under consideration. Demand for an item at time $t$ can be satisfied by an order on any day prior to $t$, but a holding cost is charged for storing the items during the intermediate period; the goal is to minimize the sum of the ordering and holding cost. Our approximation factor for both problems is $O(\log \log \min(N,T))$; this improves exponentially on the previous best results.