Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.503521
Title: Algorithms for the solution of large-scale scheduling problems
Author: Dimitriadis, Andreas Dimitriou
Awarding Body: Imperial College London (University of London)
Current Institution: Imperial College London
Date of Award: 2011
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
Abstract:
Modern multipurpose plants play a key role within the overall current climate of business globalisation, aiming to produce highly diversified products that can address the needs and demands of customers spread over wide geographical areas. The inherent size and diversity of this process gives rise to the need for planning and scheduling problems of large-scale combined production and distribution operations. In recent years, it has become possible to model combined production and distribution processes mathematically to a relatively high degree of detail. This modelling usually results in optimisation problems involving both discrete and continuous decisions. Despite much progress in numerical solution algorithms, the size and complexity of problems of industrial interest often exceed significantly those that can be tackled directly using standard algorithms and codes. This thesis is, therefore, primarily concerned with algorithms that exploit the structure of the underlying mathematical formulations to permit the practical solution of such problems. The Resource-Task Network (RTN) process representation is a general framework that has been used successfully for modelling and solving relatively small process scheduling problems. This work identifies and addresses the limitations that arise when RTNs are used for modelling large-scale production planning and scheduling problems. A number of modifications are suggested in order to make it more efficient in the representation of partial resource equivalence without losing any modelling detail. The length of the time horizon under consideration is a key factor affecting the complexity of the resulting scheduling problem. In view of this, this thesis presents two time-based decomposition approaches that attempt to solve the scheduling problem by considering only part of the time horizon in detail at any one step. The first time-based decomposition scheme is a rigorous algorithm that is guaranteed to derive optimal detailed schedules. The second scheme is a family of rolling horizon algorithms that can obtain good, albeit not necessarily optimal, detailed solutions to medium-term scheduling problems within reasonable computational times. The complexity of the process under consideration, and in particular the large numbers of interacting tasks and resources, is another factor that directly affects the difficulty of the resulting scheduling problem. Consequently, a task-based decomposition algorithm for complex RTNs is proposed, exploiting the fact that some tasks (e. g. those associated with transportation activities)
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.503521  DOI: Not available
Share: