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New models and solutions for stochas...

Rutgers The State University of New Jersey - Newark.

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New models and solutions for stochastic optimization for R&D and transportation problems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	New models and solutions for stochastic optimization for R&D and transportation problems./
作者:	Chen, Wen.
面頁冊數:	88 p.
附註:	Adviser: Michael N. Katehakis.
Contained By:	Dissertation Abstracts International70-03B.
標題:	Business Administration, Management. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3351103
ISBN:	9781109066463

New models and solutions for stochastic optimization for R&D and transportation problems.
Chen, Wen.

New models and solutions for stochastic optimization for R&D and transportation problems. - 88 p.

Adviser: Michael N. Katehakis.

Thesis (Ph.D.)--Rutgers The State University of New Jersey - Newark, 2008.

In this dissertation we develop new models and efficient solution procedures for important stochastic optimization issues in industrial R&D and transportation.

ISBN: 9781109066463Subjects--Topical Terms:

626628
Business Administration, Management.

New models and solutions for stochastic optimization for R&D and transportation problems.
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245 1 0 $a New models and solutions for stochastic optimization for R&D and transportation problems.
300 $a 88 p.
500 $a Adviser: Michael N. Katehakis.
500 $a Source: Dissertation Abstracts International, Volume: 70-03, Section: B, page: 1925.
502 $a Thesis (Ph.D.)--Rutgers The State University of New Jersey - Newark, 2008.
520 $a In this dissertation we develop new models and efficient solution procedures for important stochastic optimization issues in industrial R&D and transportation.
520 $a The first model deals with the problem of how a firm can decide to bring into the market a new product either by using internal research (IR) or by purchasing (or licensing) outside existing technology (ET). The IR consists of a known number of stages, where each stage has a random duration with known distribution. Decision epochs correspond to the start of each IR stage. The main results of this chapter are: It is shown that the optimal stopping time for IR is determined by a sequence of: "cut off" points for each stage. Finally, explicit solutions and numerical computations are given for three interesting choices for the stage duration distributions.
520 $a With the second model we study an inventory system in which the retailer during each period can further optimize its response to a shortage by either choosing to ignore the excess demand or by selecting one of a fixed number of available express channels to fulfill the excess demand. It is assumed that between periods the retailer employs an (s, S) policy, where s and S are given and the objective is to determine a vector w&ar; = (n1...,nm) to select best method to fulfill the shortage. In the case of a Geometric demand distribution we have computed the explicit value of w&ar; that maximizes the expected average profit for the system.
520 $a In the third model we study a container shipping problem in which in every period the demand is random, production is completed at some distant location and shipping is done using containers with a high transportation fee per container. We give a simple D.P. formulation for this general problem and show that the optimal container shipping policy in each time period is specified by a single number - the minimum shipping quantity. Further, we give solutions for some cases.
590 $a School code: 0461.
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650 4 $a Operations Research. $3 626629
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