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Journal ArticleDOI

Static pickup and delivery problems: a classification scheme and survey

TLDR
A general framework to model a large collection of pickup and delivery problems, as well as a three-field classification scheme for these problems, is introduced.
Abstract
Pickup and delivery problems constitute an important class of vehicle routing problems in which objects or people have to be collected and distributed. This paper introduces a general framework to model a large collection of pickup and delivery problems, as well as a three-field classification scheme for these problems. It surveys the methods used for solving them.

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Citations
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Journal ArticleDOI

Optimization of O2O Food Delivery Strategy in Smart Cities

TL;DR: In this article , an adaptive parameters genetic algorithm with local search (APGALS) was proposed to solve the online-to-online food delivery problem (OFDP) which can be viewed as a combination of variants of vehicle routing problems (VRPs).
Proceedings ArticleDOI

A parallel two-stage genetic algorithm for route planning

TL;DR: A parallel genetic algorithm that runs in two stages to solve the route planning problem of a warehouse robot to retrieve a large number of items from warehouse shelves and deliver them to the packing area is presented.
Book ChapterDOI

Evaluating the Deployment of Collaborative Logistics Models for Local Delivery Services

TL;DR: In this article, the authors evaluate several aspects for the deployment of collaborative logistics models aimed at the optimization of local delivery services in the context of the current pandemic situation and lockdowns.
References
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Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Journal ArticleDOI

Self-organized formation of topologically correct feature maps

TL;DR: In this paper, the authors describe a self-organizing system in which the signal representations are automatically mapped onto a set of output responses in such a way that the responses acquire the same topological order as that of the primary events.