The Cowl - v.82 - n.5 - Oct 5, 2017

The Cowl - student newspaper of Providence College. Volume 82, Number 5 - October 5, 2017. 24 pages

Spartan Daily, October 20, 1936

Volume 25, Issue 19https://scholarworks.sjsu.edu/spartandaily/2504/thumbnail.jp

For Our Information, May & June 1954, Vol. VI, no. 10-11

An official publication of the ILR School, Cornell University, “for the information of all faculty, staff and students

Washington University Record, January 26, 2001

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Spartan Daily, March 11, 1970

Volume 57, Issue 82https://scholarworks.sjsu.edu/spartandaily/5372/thumbnail.jp

Spartan Daily, March 11, 1970

Volume 57, Issue 82https://scholarworks.sjsu.edu/spartandaily/5372/thumbnail.jp

The Traveling Salesman Problem with Stochastic and Correlated Customers

It is well-known that the cost of parcel delivery can be reduced by designingroutes that take into account the uncertainty surrounding customers’ presences. Thus far, routing problems with stochastic customer presences have relied on the assumption that all customer presences are independent from each other. However, the notion that demographic factors retain predictive power for parcel-delivery efficiency suggests that shared characteristics can be exploited to map dependencies between customer presences. This paper introduces the correlated probabilistic traveling salesman problem (CPTSP). The CPTSP generalizes the traveling salesman problem with stochastic customer presences, also known as the probabilistic traveling salesman problem (PTSP), to account for potentialcorrelations between customer presences. I propose a generic and flexible model formulation for the CPTSP using copulas that maintains computational and mathematical tractability in high-dimensional settings. I also present several adaptations of existing exact and heuristic frameworks to solve the CPTSP effectively. Computational experiments on real-world parcel-delivery data reveal that correlations between stochastic customer presences do not always affect route decisions, but could have a considerable impact on route costestimates