Kis, Tamás and Kovács, András (2012) On bilevel machine scheduling problems. OR SPECTRUM: QUANTITATIVE APPROACHES IN MANAGEMENT, 34 (1). pp. 43-68. ISSN 0171-6468 10.1007/s00291-010-0219-y

Full text not available from this repository.

Abstract

Bilevel scheduling problems constitute a hardly studied area of scheduling theory. In this paper, we summarise the basic concepts of bilevel optimisation, and discuss two problem classes for which we establish various complexity and algorithmic results. The first one is the bilevel total weighted completion time problem in which the leader assigns the jobs to parallel machines and the follower sequences the jobs assigned to each machine. Both the leader and the follower aims to minimise the total weighted completion time objective, but with different job weights. When the leader's weights are arbitrary, the problem is NP-hard. However, when all the jobs are of unit weight for the leader, we provide a heuristic algorithm based on iterative LP-rounding along with computational results, and provide a sufficient condition when the LP-solution is integral. In addition, if the follower weights induce a monotone (increasing or decreasing) processing time order in any optimal solution, the problem becomes polynomially solvable. As a by-product, we characterise a new polynomially solvable special case of the MAX m-CUT problem, and provide a new linear programming formulation for theP∑ jC jproblem. Finally, we present some results on the bilevel order acceptance problem, where the leader decides on the acceptance of orders and the follower sequences the jobs. Each job has a deadline and if a job is accepted, it cannot be late. The leader's objective is to maximise the total weight of accepted jobs, whereas the follower aims at minimising the total weighted job completion times. For this problem, we generalise some known single-level machine scheduling algorithms. © 2010 Springer-Verlag.

Item Type:	ISI Article
Uncontrolled Keywords:	Scheduling, MAX m-CUT, Linear programming, Bilevel optimisation, Approximation algorithms
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Divisions:	Research Laboratory on Engineering & Management Intelligence
Depositing User:	EPrints Admin
Date Deposited:	11 Dec 2012 16:04
Last Modified:	26 Nov 2016 16:11
URI:	https://eprints.sztaki.hu/id/eprint/5796

Update Item