Risk Averse Scheduling with Scenarios

Mikita Hradovich (), Adam Kasperski and Paweł Zieliński ()
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Mikita Hradovich: Wrocław University of Science and Technology
Paweł Zieliński: Wrocław University of Science and Technology

A chapter in Operations Research Proceedings 2017, 2018, pp 435-441 from Springer

Abstract: Abstract This paper deals with a class of scheduling problems with uncertain job processing times and due dates. The uncertainty is specified in the form of discrete scenario set. A probability distribution in the scenario set is known. Thus the cost of a given schedule is then a discrete random variable with known probability distribution. In order to compute a solution the popular risk criteria, such as the value at risk and the conditional value at risk, are applied. These criteria allow us to establish a link between the very conservative maximum criterion, typically used in robust optimization, and the expectation, commonly used in the stochastic approach. Using them we can take a degree of risk aversion of decision maker into account. In this paper, basic single machine scheduling problems with the risk criteria for choosing a solution are considered. Various positive complexity results are provided for them.

Keywords: Optimization under uncertainty; Scheduling; Approximation algorithms (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-319-89920-6_58

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DOI: 10.1007/978-3-319-89920-6_58

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