Publication

Demand-based scheduling

Michel Bierlaire
2015
Talks

Abstract

Demand-based scheduling refers to the set of transportation problems that explicitly take into account individual behaviour. In particular, performance indicators of operational decisions combine the actual cost of the operations with an explicit measure of passenger satisfaction. Moreover, it is necessary to account for the uncertainty related to behavioral aspects. In this presentation, we present the structure of these problems and distinguish them from other demand-based problems. We also demonstrate some of its applications in railway industries. Also, we discuss about passengers itinerary choice and how it could be affected by train schedule..

Official source

https://infoscience.epfl.ch/entities/publication/3fa3eb58-7640-463b-b980-98cfe0b9fc75

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Michel Bierlaire
2015
Talks

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/3fa3eb58-7640-463b-b980-98cfe0b9fc75

About this result

Related concepts (21)

Supply and demand

In microeconomics, supply and demand is an economic model of price determination in a market. It postulates that, holding all else equal, in a competitive market, the unit price for a particular good, or other traded item such as labor or liquid financial assets, will vary until it settles at a point where the quantity demanded (at the current price) will equal the quantity supplied (at the current price), resulting in an economic equilibrium for price and quantity transacted.

Behavioral economics

Behavioral economics studies the effects of psychological, cognitive, emotional, cultural and social factors in the decisions of individuals or institutions, and how these decisions deviate from those implied by classical economic theory. Behavioral economics is primarily concerned with the bounds of rationality of economic agents. Behavioral models typically integrate insights from psychology, neuroscience and microeconomic theory. The study of behavioral economics includes how market decisions are made and the mechanisms that drive public opinion.

Uncertainty

Uncertainty refers to epistemic situations involving imperfect or unknown information. It applies to predictions of future events, to physical measurements that are already made, or to the unknown. Uncertainty arises in partially observable or stochastic environments, as well as due to ignorance, indolence, or both. It arises in any number of fields, including insurance, philosophy, physics, statistics, economics, finance, medicine, psychology, sociology, engineering, metrology, meteorology, ecology and information science.