Economic Lot Size Formula Under VMI Program with Poisson Demand

Moarefdoost, M. Mohsen; Zokaee, Shiva; Haji, Rasoul

doi:10.1007/s13369-014-1330-1

Cited by 2 publications

(1 citation statement)

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“…More specifically, we emphasize algorithmic methods while the current literature focuses on proving structural properties. Generator disruptions in power networks are analogous to supply disruptions in the supply chain management literature, as studied by Parlar et al , Güllü et al , Tomlin , Snyder et al , Moarefdoost et al and others, and this analogy is exploited in our heuristics.…”

Section: Introductionmentioning

confidence: 99%

Generation and storage dispatch in electricity networks with generator disruptions

Moarefdoost

Snyder

2015

Naval Research Logistics

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We present methods for optimizing generation and storage decisions in an electricity network with multiple unreliable generators, each colocated with one energy storage unit (e.g., battery), and multiple loads under power flow constraints. Our model chooses the amount of energy produced by each generator and the amount of energy stored in each battery in every time period in order to minimize power generation and storage costs when each generator faces stochastic Markovian supply disruptions. This problem cannot be optimized easily using stochastic programming and/or dynamic programming approaches. Therefore, in this study, we present several heuristic methods to find an approximate optimal solution for this system. Each heuristic involves decomposing the network into several single‐generator, single‐battery, multiload systems and solving them optimally using dynamic programming, then obtaining a solution for the original problem by recombining. We discuss the computational performance of the proposed heuristics as well as insights gained from the models. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 493–511, 2015

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