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Probability theory. A Markov chain or Markov process is a stochastic process describing a sequence of possible events in which the probability of each event depends only on the state attained in the previous event. Informally, this may be thought of as, "What happens next depends only on the state of affairs now."
Markov model. In probability theory, a Markov model is a stochastic model used to model pseudo-randomly changing systems. It is assumed that future states depend only on the current state, not on the events that occurred before it (that is, it assumes the Markov property). Generally, this assumption enables reasoning and computation with the ...
Continuous-time Markov chain. A continuous-time Markov chain (CTMC) is a continuous stochastic process in which, for each state, the process will change state according to an exponential random variable and then move to a different state as specified by the probabilities of a stochastic matrix. An equivalent formulation describes the process as ...
Markov property. A single realisation of three-dimensional Brownian motion for times 0 ≤ t ≤ 2. Brownian motion has the Markov property, as the displacement of the particle does not depend on its past displacements. In probability theory and statistics, the term Markov property refers to the memoryless property of a stochastic process ...
The Supply Chain Operations Reference (SCOR) model is a process reference model originally developed and endorsed by the Supply Chain Council, now a part of ASCM, as the cross-industry, standard diagnostic tool for supply chain management. [1] The SCOR model describes the business activities associated with satisfying a customer's demand, which ...
t. e. Supply and demand stacked in a conceptual chain. A supply chain is a complex logistics system that consists of facilities that convert raw materials into finished products and distribute them [ 1 ] to end consumers [ 2 ] or end customers. [ 3 ] Meanwhile, supply chain management deals with the flow of goods in distribution channels within ...
Figure 1. Probabilistic parameters of a hidden Markov model (example) X — states y — possible observations a — state transition probabilities b — output probabilities. In its discrete form, a hidden Markov process can be visualized as a generalization of the urn problem with replacement (where each item from the urn is returned to the original urn before the next step). [7]
Push–pull strategy. The original meaning of push and pull, as used in operations management, logistics and supply chain management. In the pull system production orders begin upon inventory reaching a certain level, while on the push system production begins based on demand (forecasted or actual demand). The CONWIP is a hybrid between a pure ...