On a borderline between the NP-hard and polynomial-time solvable cases of the flow shop with job-dependent storage requirements

TL;DR

This paper investigates a two-machine flow shop scheduling problem with job-dependent storage constraints, analyzing how storage capacity bounds influence the problem's computational complexity, which is generally NP-hard.

Contribution

It provides a detailed complexity analysis of the flow shop problem with storage limits, identifying conditions under which the problem transitions between NP-hard and polynomial solvability.

Findings

Complexity depends on storage capacity bounds.

NP-hardness is established for general cases.

Certain bounds lead to polynomial-time solutions.

Abstract

The paper is concerned with the two-machine flow shop, where each job requires an additional resource (referred to as storage space) from the start of its first operation till the end of its second operation. The storage requirement of a job is determined by the processing time of its first operation. At any point in time, the total consumption of this additional resource cannot exceed a given limit (referred to as the storage capacity). The goal is to minimise the makespan, i.e. to minimise the time needed for the completion of all jobs. This problem is NP-hard in the strong sense. The paper analyses how the parameter - a lower bound on the storage capacity specified in terms of the processing times, affects the computational complexity.