A model-based algorithm for the Probabilistic Orienteering Problem

IF 4.1 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Operations Research Pub Date : 2024-12-13 DOI:10.1016/j.cor.2024.106947

Roberto Montemanni , Derek H. Smith

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引用次数: 0

Abstract

The Orienteering Problem is a routing problem aiming at selecting a subset of a given set of customers to be visited within a given time budget, so that a total revenue is maximized. Multiple variants of the problem have been studied. The Probabilistic Orienteering Problem is one of these variants, where customers will require a visit according to a certain given probability. Stochasticity makes the model more practical, but concurrently more difficult to solve. Effective approaches to solve the problem potentially lead to higher quality planning in real-life logistics, thanks to the exploitation of the probabilistic informations that can normally be derived from historical data.

In this paper we present an iterative model-based algorithm that solves a sequence of deterministic problems and is able to retrieve and certify optimal solutions if run for sufficient time. Experimental results show that the new approach is performing well when compared against both the exact (proven optimality) and heuristic (high quality solutions) algorithms available in the literature.

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来源期刊

Computers & Operations Research 工程技术-工程：工业

CiteScore

8.60

自引率

8.70%

发文量

292

审稿时长

8.5 months

期刊介绍： Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.