A Constraint-directed Local Search Approach to Nurse Rostering Problems

In this paper, we investigate the hybridization of constraint programming and local search techniques within a large neighbourhood search scheme for solving highly constrained nurse rostering problems. As identified by the research, a crucial part of the large neighbourhood search is the selection of the fragment (neighbourhood, i.e. the set of variables), to be relaxed and re-optimized iteratively. The success of the large neighbourhood search depends on the adequacy of this identified neighbourhood with regard to the problematic part of the solution assignment and the choice of the neighbourhood size. We investigate three strategies to choose the fragment of different sizes within the large neighbourhood search scheme. The first two strategies are tailored concerning the problem properties. The third strategy is more general, using the information of the cost from the soft constraint violations and their propagation as the indicator to choose the variables added into the fragment. The three strategies are analyzed and compared upon a benchmark nurse rostering problem. Promising results demonstrate the possibility of future work in the hybrid approach

Models, methods and algorithms for supply chain planning

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.An outline of supply chains and differences in the problem types is given. The motivation for a generic framework is discussed and explored. A conceptual model is presented along with it application to real world situations; and from this a database model is developed. A MIP and CP implementations are presented; along with alternative formulation which can be use to solve the problems. A local search solution algorithm is presented and shown to have significant benefits. Problem instances are presented which are used to validate the generic models, including a large manufacture and distribution problem. This larger problem instance is not only used to explore the implementation of the models presented, but also to explore the practically of the use of alternative formulation and solving techniques within the generic framework and the effectiveness of such methods including the neighbourhood search solving method. A stochastic dimension to the generic framework is explored, and solution techniques for this extension are explored, demonstrating the use of solution analysis to allow problem simplification and better solutions to be found. Finally the local search algorithm is applied to the larger models that arise from inclusion of scenarios, and the methods is demonstrated to be powerful for finding solutions for these large model that were insoluble using the MIP on the same hardware

Models, methods and algorithms for supply chain planning

An outline of supply chains and differences in the problem types is given. The motivation for a generic framework is discussed and explored. A conceptual model is presented along with it application to real world situations; and from this a database model is developed. A MIP and CP implementations are presented; along with alternative formulation which can be use to solve the problems. A local search solution algorithm is presented and shown to have significant benefits. Problem instances are presented which are used to validate the generic models, including a large manufacture and distribution problem. This larger problem instance is not only used to explore the implementation of the models presented, but also to explore the practically of the use of alternative formulation and solving techniques within the generic framework and the effectiveness of such methods including the neighbourhood search solving method. A stochastic dimension to the generic framework is explored, and solution techniques for this extension are explored, demonstrating the use of solution analysis to allow problem simplification and better solutions to be found. Finally the local search algorithm is applied to the larger models that arise from inclusion of scenarios, and the methods is demonstrated to be powerful for finding solutions for these large model that were insoluble using the MIP on the same hardware.EThOS - Electronic Theses Online ServiceGBUnited Kingdo