Node-Level Energy Management for Sensor Networks in the Presence of Multiple Applications
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Stochastic Networks: Admission and Routing Using Penalty Functions
Queueing Systems: Theory and Applications
Node-level energy management for sensor networks in the presence of multiple applications
Wireless Networks - Special issue: Pervasive computing and communications
A multiple-choice secretary algorithm with applications to online auctions
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Online pricing for web service providers
Proceedings of the 2006 international workshop on Economics driven software engineering research
Simulation optimization using tabu search: an emperical study
WSC '05 Proceedings of the 37th conference on Winter simulation
Fundamenta Informaticae
Exploiting Knowledge About Future Demands for Real-Time Vehicle Dispatching
Transportation Science
Online auctions and generalized secretary problems
ACM SIGecom Exchanges
Online network design with outliers
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
Knapsack problem with probability constraints
Journal of Global Optimization
A case-based seat allocation system for airline revenue management
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Critical level policies in lost sales inventory systems with different demand classes
EPEW'11 Proceedings of the 8th European conference on Computer Performance Engineering
Fundamenta Informaticae
Planning in logistics: a survey
Proceedings of the 10th Performance Metrics for Intelligent Systems Workshop
A Lagrangian approach to dynamic resource allocation
Proceedings of the Winter Simulation Conference
International Journal of Information Technology Project Management
An improved firefly algorithm for solving dynamic multidimensional knapsack problems
Expert Systems with Applications: An International Journal
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The Dynamic and Stochastic Knapsack Problem (DSKP) is defined as follows. Items arrive according to a Poisson process in time. Each item has a demand (size) for a limited resource (the knapsack) and an associated reward. The resource requirements and rewards are jointly distributed according to a known probability distribution and become known at the time of the item's arrival. Items can be either accepted or rejected. If an item is accepted, the item's reward is received; and if an item is rejected, a penalty is paid. The problem can be stopped at any time, at which time a terminal value is received, which may depend on the amount of resource remaining. Given the waiting cost and the time horizon of the problem, the objective is to determine the optim al policy that maximizes the expected value (rewards minus costs) accumulated. Assuming that all items have equal sizes but random rewards, optimal solutions are derived for a variety of cost structures and time horizons, and recursive algorithms for computing them are developed. Optimal closed-form solutions are obtained for special cases. The DSKP has applications in freight transportation, in scheduling of batch processors, in selling of assets, and in selection of investment projects.