Abstract

Given a set S of integers whose sum is zero, consider the problem of finding a permutation of these integers such that (i) all prefix sums of the ordering are nonnegative and (ii) the maximum value of a prefix sum is minimized. Kellerer et al. call this problem the stock size problem and showed that it can be approximated to within 3/2. They also showed that an approximation ratio of 2 can be achieved via several simple algorithms. We consider a related problem, which we call the alternating stock size problem , where the numbers of positive and negative integers in the input set S are equal. The problem is the same as that shown earlier, but we are additionally required to alternate the positive and negative numbers in the output ordering. This problem also has several simple 2-approximations. We show that it can be approximated to within 1.79. Then we show that this problem is closely related to an optimization version of the gasoline puzzle due to Lovász, in which we want to minimize the size of the gas tank necessary to go around the track. We present a 2-approximation for this problem, using a natural linear programming relaxation whose feasible solutions are doubly stochastic matrices. Our novel rounding algorithm is based on a transformation that yields another doubly stochastic matrix with special properties, from which we can extract a suitable permutation.

Highlights

  • Suppose there is a set of jobs that can be processed in any order

  • We show that this problem is closely related to an optimization version of the gasoline puzzle due to Lovász, in which we want to minimize the size of the gas tank necessary to go around the track

  • Each job requires a specified amount of a particular resource, e.g. gasoline, which can be supplied in an amount chosen from a specified set of quantities

Read more

Summary

Introduction

Suppose there is a set of jobs that can be processed in any order. Each job requires a specified amount of a particular resource, e.g. gasoline, which can be supplied in an amount chosen from a specified set of quantities. The goal is to order the jobs and the replenishment amounts so that the required quantity of the resource is always available for the job being processed and so that the storage space is never exceeded. (We sometimes use μ = max{μx, μy}.) Since both μx and μy are lower bounds on the value S∗ of an optimal solution, this shows that the problem can be approximated to within a factor of 2. They presented algorithms with approximation guarantees of 8/5 and 3/2 [11]

The Alternating Stock Size Problem
Connections to the Gasoline Puzzle
The Gasoline Problem
Generalizations of the Gasoline Problem
Related Work
Algorithms for the Alternating Stock Size Problem
The Pairing Algorithm
Lower Bound for the Alternating Stock Size Problem
Alternating Batches
Gasoline Problem
Transformation
Rounding
Conclusions
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.