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Dynamic and stochastic models with f...

Purdue University.

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Dynamic and stochastic models with freight distribution applications.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Dynamic and stochastic models with freight distribution applications./
作者:	Kleywegt, Anton Jan.
面頁冊數:	222 p.
附註:	Major Professor: Jason D. Papastavrou.
Contained By:	Dissertation Abstracts International57-11B.
標題:	Engineering, Industrial. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=9713537
ISBN:	0591211955

Dynamic and stochastic models with freight distribution applications.
Kleywegt, Anton Jan.

Dynamic and stochastic models with freight distribution applications. - 222 p.

Major Professor: Jason D. Papastavrou.

Thesis (Ph.D.)--Purdue University, 1996.

This research is motivated by the need for decision support tools to manage complex freight distribution operations. The fact that freight distribution is such an important economic activity, makes this research both worthwhile and rewarding.

ISBN: 0591211955Subjects--Topical Terms:

626639
Engineering, Industrial.

Dynamic and stochastic models with freight distribution applications.
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500 $a Source: Dissertation Abstracts International, Volume: 57-11, Section: B, page: 7161.
502 $a Thesis (Ph.D.)--Purdue University, 1996.
520 $a This research is motivated by the need for decision support tools to manage complex freight distribution operations. The fact that freight distribution is such an important economic activity, makes this research both worthwhile and rewarding.
520 $a In the first part of this research, a generic resource allocation problem in a dynamic and stochastic environment is studied. This problem is motivated by the issues facing a manager of a transportation operation regarding the acceptance of loads and the dispatching of a vehicle. Because it has applications in many other areas, such as the scheduling of batch processors, the selling of assets, and the selection of investment projects, it is called the Dynamic and Stochastic Knapsack Problem (DSKP). The DSKP is analyzed for both the infinite horizon and the finite horizon cases. It is shown that an optimal acceptance rule is given by a threshold rule. The optimal stopping time is also easily determined, and has the convenient property that under typical conditions, only times right after a demand has been accepted need to be considered as potential stopping times. Efficient algorithms for computing optimal solutions are proposed. These algorithms compute the value corresponding to each state of the process only once, in contrast with the classical iterative algorithms that are used to solve dynamic programming problems. It is established that the optimal value and optimal threshold have a number of interesting monotonicity and convexity properties.
520 $a In the second part of this research, a distribution problem with a number of terminals and a fleet of vehicles is studied. This problem is called the Dynamic and Stochastic Distribution Problem (DSDP). A Markov decision process model is developed, and optimal policies are characterized. It is shown that the classical algorithms for solving Markov decision processes converge if applied to the DSDP, in spite of the fact that the DSDP does not satisfy all the assumptions made in the traditional convergence proofs. An algorithm that exploits the structure of the DSDP is developed. The proposed algorithm consistently outperforms the classical algorithms in computational experiments.
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