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One of the few books that focuses on the applications of the RNA
seq technique in drug discovery and development. Comprehensive and
timely publication which relates RNA sequencing to drug targets,
mechanisms of action and resistance The editor has extensive
experience in the field of computational medicinal chemistry,
computational biophysics and bioinformatics. Chapter authors are at
the frontline of the academic and industrial science in this
particular area of RNA sequencing
Inventory management is concerned with matching supply with demand
and a central problem in Operations Management. The problem is to
find the amount to be produced or purchased in order to maximize
the total expected profit or minimize the total expected cost. Over
the past two decades, several variations of the formula appeared,
mostly in trade journals written by and for inventory managers. A
critical assumption in the inventory literature is that the demands
in different periods are independent and identically distributed.
However, in real life, demands may depend on environmental
considerations or the events in the world such as the weather, the
state of economy, etc. Moreover, these events are represented by
stochastic processes - exogenous or controlled. In Markovian Demand
Inventory Models, the authors are concerned with inventory models
where these world events are modeled by Markov processes. Their
research on Markovian demand inventory models was carried out over
a period of ten years beginning in the early nineties. They
demonstrate that the optimality of (s, S)-type policies, or
base-stock policies (i.e., s = S) when there are no fixed ordering
costs with the provision that the policy parameters s and S depend
on the current state of the Markov process representing the
environment. Models allowing backorders when the entire demand
cannot be filled from the available inventory as well as those when
the current demand is lost are considered. As for cost criteria, we
treat both the minimization of the expected total discounted cost
and the long-run average cost. The average-cost criterion is
mathematically more difficult than the discounted cost criteria.
Finally, wegeneralize the usual assumptions on holding and shortage
costs and on demands that are made in the literature.
This text provides a superbly researched insight into Markovian
demand inventory models. The result of ten years of research, this
work covers all aspects of demand inventory where they are modeled
by Markov processes. Inventory management is concerned with
matching supply with demand and is a central problem in Operations
Management. The central problem is to find the amount to be
produced or purchased in order to maximize the total expected
profit, or minimize the total expected cost.
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