Browsing by Author "De Villiers, Anton Pierre"
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- ItemEdge criticality in secure graph domination(Stellenbosch : Stellenbosch University, 2014-12) De Villiers, Anton Pierre; Van Vuuren, J. H.; Burger, A. P.; Stellenbosch University. Faculty of Engineering. Department of Industrial Engineering.ENGLISH ABSTRACT: The domination number of a graph is the cardinality of a smallest subset of its vertex set with the property that each vertex of the graph is in the subset or adjacent to a vertex in the subset. This graph parameter has been studied extensively since its introduction during the early 1960s and finds application in the generic setting where the vertices of the graph denote physical entities that are typically geographically dispersed and have to be monitored efficiently, while the graph edges model links between these entities which enable guards, stationed at the vertices, to monitor adjacent entities. In the above application, the guards remain stationary at the entities. In 2005, this constraint was, however, relaxed by the introduction of a new domination-related parameter, called the secure domination number. In this relaxed, dynamic setting, each unoccupied entity is defended by a guard stationed at an adjacent entity who can travel along an edge to the unoccupied entity in order to resolve a security threat that may occur there, after which the resulting configuration of guards at the entities is again required to be a dominating set of the graph. The secure domination number of a graph is the smallest number of guards that can be placed on its vertices so as to satisfy these requirements. In this generalised setting, the notion of edge removal is important, because one might seek the cost, in terms of the additional number of guards required, of protecting the complex of entities modelled by the graph if a number of edges in the graph were to fail (i.e. a number of links were to be eliminated form the complex, thereby disqualifying guards from moving along such disabled links). A comprehensive survey of the literature on secure graph domination is conducted in this dissertation. Descriptions of related, generalised graph protection parameters are also given. The classes of graphs with secure domination number 1, 2 or 3 are characterised and a result on the number of defenders in any minimum secure dominating set of a graph without end-vertices is presented, after which it is shown that the decision problem associated with computing the secure domination number of an arbitrary graph is NP-complete. Two exponential-time algorithms and a binary programming problem formulation are presented for computing the secure domination number of an arbitrary graph, while a linear algorithm is put forward for computing the secure domination number of an arbitrary tree. The practical efficiencies of these algorithms are compared in the context of small graphs. The smallest and largest increase in the secure domination number of a graph are also considered when a fixed number of edges are removed from the graph. Two novel cost functions are introduced for this purpose. General bounds on these two cost functions are established, and exact values of or tighter bounds on the cost functions are determined for various infinite classes of special graphs. Threshold information is finally established in respect of the number of possible edge removals from a graph before increasing its secure domination number. The notions of criticality and stability are introduced and studied in this respect, focussing on the smallest number of arbitrary edges whose deletion necessarily increases the secure domination number of the resulting graph, and the largest number of arbitrary edges whose deletion necessarily does not increase the secure domination number of the resulting graph.
- ItemMinimising the total travel distance to pick orders on a unidirectional picking line(Stellenbosch : Stellenbosch University, 2012-03) De Villiers, Anton Pierre; Visagie, S. E.; Stellenbosch University. Faculty of Economic and Management Sciences. Dept. of Logistics.ENGLISH ABSTRACT: Order picking is the most important activity in distribution centres. It involves the process of retrieving products from storage in response to a speci c customer request. The order picking system in a distribution centre used by Pep Stores Ltd. (Pep), located in Durban, South Africa, is considered. The order picking system in Pep utilises picking lines. The system requires that the pickers move in a clockwise direction around the picking line. The planning of picking lines may be divided into three tiers of decisions. The rst tier determines which Stock Keeping Units (SKUs) should be allocated to which picking line and is known as the SKU to Picking Line Assignment Problem (SPLAP). The second tier, the SKU Location Problem (SLP), considers the positioning of the various SKUs in a picking line. The nal tier considers the sequencing of the orders for pickers within a picking line and is referred to as the Order Sequencing Problem (OSP). Collectively, these three tiers aim to achieve the objective of picking all the SKUs for all the orders in the shortest possible time. The decisions associated with each tier are made sequentially during the planning of a picking line. Each problem therefore relies on the information generated by its predecessing tier(s). Initially the OSP is addressed. A number of heuristic and metaheuristic approaches are presented, together with an exact formulation to solve this tier. The size of the problem is reduced by using a relaxation of the problem that may be solved exactly. A number of greedy tour construction heuristics, a scope and ranking algorithm, methods based on awarding starting locations with respect to preference ratios and a modi ed assignment approach was used to solve the OSP. Furthermore, a tabu search, simulated annealing, genetic algorithm and a generalised extremal optimisation approach are used to solve the OSP. The solution quality and computational times of all the approaches are compared for the data provided by Pep, with the generalised extremal optimisation approach delivering the best solution quality. Two methods from the literature was used to model the SLP, whereafter an ant colony system was used to maximise the number of orders in common between adjacent SKUs. A number of agglomerative clustering algorithms were used from which dendrograms could be constructed. Two novel heuristic clustering algorithms were considered. The rst heuristic calculates a distance between two clusters as the set of orders that have to collect all the SKUs in both clusters, whereas the second method is based upon the frequency of SKUs within a cluster. Little or no improvement was achieved in most cases. The SPLAP was introduced by means of a number of possibilities of how to formulate objectives. A possible exact formulation is presented, followed by a nearest neighbour search, which was initially used to construct new picking lines based on all data sets. A di erent approach was then taken by means of a tabu search where the waves of two or three picking lines were altered. Signi cant savings may be incurred for large data sets.