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Mathematical Formulations for Complex Resource Scheduling Problems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mathematical Formulations for Complex Resource Scheduling Problems./
作者:	Lalita, T. R.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:	219 p.
附註:	Source: Dissertations Abstracts International, Volume: 83-06, Section: B.
Contained By:	Dissertations Abstracts International83-06B.
標題:	Scheduling. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28843871
ISBN:	9798496588980

Mathematical Formulations for Complex Resource Scheduling Problems.
Lalita, T. R.

Mathematical Formulations for Complex Resource Scheduling Problems. - Ann Arbor : ProQuest Dissertations & Theses, 2021 - 219 p.

Source: Dissertations Abstracts International, Volume: 83-06, Section: B.

Thesis (Ph.D.)--Indian Statistical Institute - Kolkata, 2021.

This item must not be sold to any third party vendors.

This thesis deals with development of effective models for large scale real-world resource scheduling problems. Efficient utilization of resources is crucial for any organization or industry as resources are often scarce. Scheduling them in an optimal way can not only take care of the scarcity but has potential economic benefits. Optimal utilization of resources reduces costs and thereby provides a competitive edge in the business world. Resources can be of different types such as human (personnel-skilled and unskilled), financial(budgets), materials, infrastructures(airports and seaports with designed facilities, windmills, warehouses' area, hotel rooms etc) and equipment (microprocessors, cranes, machinery, aircraft simulators for training), etc. Typically, scheduling of resources is done over a period of time (planning horizon), but in many cases there are other dimensions to the problem induced by limited resources.In one class of resource scheduling where resources are facilities, there is a special requirement that the limited resources are assigned to tasks in an adjacent manner. This class is known as adjacent resource scheduling (ARS) (see Duin and Sluis (2006)). There are numerous applications to this model but in this thesis we are concerned with two important applications of this class of problems. The first one is assigning check-in counters to flight departures at airports. Here the counters assigned to each departure must be adjacent (physically). Because the number of counters is limited in any given airport, counter number (or its id) becomes a second dimension in this assignment and scheduling problem. The second application is in the cargo ship management. In cargo ship terminals, ships are moored to the quay for loading and unloading operations. For modelling purposes, the quay is discretised into berth sections of unit length. A ship of length k units requires a space of k contiguous (adjacent) berth sections in the quay. The limited quay space has to be reused to accommodate multiple ships over the planning horizon. Thus, quay space becomes a second dimension in this problem. In addition, the loading and unloading operations are performed by cranes which are fixed on rails. This restricts the free movement of cranes and they cannot bypass their adjacent ones. This adds a third dimension to the berth and crane allocation and scheduling problem. The cranes serving a ship in this set-up, therefore, must be adjacent. Thus, a third dimension to the problem is induced by limited number of movement-restricted cranes. There are a number of other applications of ARS. Some other applications include: (i) private warehouses let out adjacent storage spaces to customers requiring temporary storage spaces, (ii) hotel room reservations for different customers requiring multiple adjacent rooms, (iii) gate allocation to flight arrivals requiring adjacent or nearby gates for connecting flights, etc.Another class of resource scheduling problems to which this thesis makes an important contribution is the integrated staff and task scheduling problem (ISTSP). In this problem, the resources are staff or workers who work in shifts. Given a set of tasks to be performed over a given period of time, the problem seeks minimum number of workers to complete the tasks. Each task comes with the specification of (i) a time interval during which the task must commence and (ii) duration of the task and the number of workers required for it during each time period.

ISBN: 9798496588980Subjects--Topical Terms:

750729
Scheduling.

Mathematical Formulations for Complex Resource Scheduling Problems.
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