This thesis is concerned with the Resident Scheduling Problem (RSP) in which a good schedule is desired that will meet both departmental requirements and residents' preferences. Three scenarios that represent most situations and account for various departmental requirements and needs are described. Although similar scheduling problems are considered in the literature, no analysis exists that adequately deals with this specific problem. The problem is modeled as a mixed-integer program (MIP) and heuristic solution procedures are developed for the different identified scheduling scenarios. These procedures exploit the network structure of the problem which is an important feature that enhances problem solvability. For the sake of comparison, the problem is also solved exactly via the CPLEX-MIP package. The contribution of this work is important since many hospitals are still utilizing manual techniques in preparing their own schedules, expending considerable effort and time with less scheduling flexibility. / Master of Science

Les terminaux à conteneurs utilisent les nouvelles technologies (EDI, RFID et GPS) pour échanger des données avec leurs partenaires, pour localiser les conteneurs et leurs équipements dans le terminal, et pour automatiser des tâches. Dans cette thèse, nous montrons comment ces informations peuvent être utilisées dans la gestion des opérations.La première partie utilise les informations sur les volumes annoncés pour affecter des ressources internes dans le but de minimiser le retard global au terminal. Nous représentons cette problématique à l'aide d'un problème de flot que nous implémentons comme programme linéaire mixte. Une étude de cas est réalisée pour un terminal du Grand Port Maritime de Marseille. En outre, nous combinons le problème d'affectation de ressources avec le dimensionnement d'un système de rendez-vous. Ceci permet de minimiser le retard global.La deuxième partie utilise les informations sur les conteneurs à retirer et leurs emplacements pour optimiser le déstockage. Le but est de retirer tous les conteneurs d'une rangée en minimisant le nombre de repositionnements parasites. Nous améliorons un modèle binaire, proposons une approche exacte de type branch and price - avec un sous-problème binaire et deux variantes d'un sous-problème énumératif - et en dérivons une approche heuristique - avec un sous-problème heuristique. L'approche exacte ne résout que les petites instances ; l'approche heuristique obtient des résultats satisfaisants mais devra être améliorée. Nous nous intéressons aussi à la version dynamique du problème où les informations sur les conteneurs à retirer arrivent petit à petit et comparons différentes stratégies de repositionnement. / Container terminals use intelligent freight technologies (e.g., EDI, RFID and GPS) to exchange data with their partners, to locate containers and equipment within the terminal, and to automate tasks. This thesis illustrated, via two examples, how this data may be used to optimize operations at the terminal.The first part uses information on announced volumes to allocate internal handling equipment. The objective is to minimize overall delays at the terminal. The problem is represented as a network flow problem and implemented as a linear mixed integer programming model. A case study for a terminal at the Grand Port Maritime de Marseille is carried out. We also showed that combining the allocation problem with the dimensioning of a truck appointment system may reduce overall delays at the terminal. The second part uses information on announced container retrievals and container positions to improve retrieval operations. The objective is to retrieve containers from a bay in a given sequence with a minimum number of parasite relocations. We improve an existing binary programming model and introduce an exact branch and price approach - with a binary subproblem and two variants of an enumerative subproblem - and a heuristic branch and price approach - with a heuristic subproblem. The exact approach solves only small instances; the heuristic approach performs well on several instances, but should be improved further. We also deal with a dynamic version of the problem where the retrieval order becomes revealed over time and evaluate different relocation strategies for this case.

Container terminals use intelligent freight technologies (e.g., EDI, RFID and GPS) to exchange data with their partners, to locate containers and equipment within the terminal, and to automate tasks. This thesis illustrated, via two examples, how this data may be used to optimize operations at the terminal.The first part uses information on announced volumes to allocate internal handling equipment. The objective is to minimize overall delays at the terminal. The problem is represented as a network flow problem and implemented as a linear mixed integer programming model. A case study for a terminal at the Grand Port Maritime de Marseille is carried out. We also showed that combining the allocation problem with the dimensioning of a truck appointment system may reduce overall delays at the terminal. The second part uses information on announced container retrievals and container positions to improve retrieval operations. The objective is to retrieve containers from a bay in a given sequence with a minimum number of parasite relocations. We improve an existing binary programming model and introduce an exact branch and price approach - with a binary subproblem and two variants of an enumerative subproblem - and a heuristic branch and price approach - with a heuristic subproblem. The exact approach solves only small instances; the heuristic approach performs well on several instances, but should be improved further. We also deal with a dynamic version of the problem where the retrieval order becomes revealed over time and evaluate different relocation strategies for this case.

In this study, the effect of implementing Network Coding on the aggregated throughput in Wireless Mesh Networks, was examined. Wireless Mesh Networks (WMNs) are multiple hop wireless networks, where routing through any node is possible. The implication of this characteristic, is that messages flow across the points where it would have been terminated in conventional wireless networks. User nodes in conventional wireless networks only transmit and receive messages from an Access Point (AP), and discard any messages not intended for them. The result is an increase in the volume of network traffic through the links of WMNs. Additionally, the dense collection of multiple RF signals propagating through a shared wireless medium, contributes to the situation where the links become saturated at levels below their capacity. The need exists to examine methods that will improve the utilisation of the shared wireless medium in WMNs. Network Coding is a coding and decoding technique at the network level of the OSI stack, aimed to improve the boundaries of saturated links. The technique implies that the bandwidth is simultaneously shared amongst separate message flows, by combining these flows at common intermediate nodes. The number of transmissions needed to convey information through the network, is decreased by Network Coding. The result is in an improvement of the aggregated throughput. The research approach followed in this dissertation, includes the development of a model that investigates the aggregated throughput performance of WMNs. The scenario of the model, followed a typical example of indoors WMN implementations. Therefore, the physical environment representation of the network elements, included an indoors log–distance path loss channel model, to account for the different effects such as: power absorption through walls; and shadowing. Network functionality in the model was represented through a network flow programming problem. The problem was concerned with determining the optimal amount of flow represented through the links of the WMN, subject to constraints pertaining to the link capacities and mass balance at each node. The functional requirements of the model stated that multiple concurrent sessions were to be represented. This condition implied that the network flow problem had to be a multi–commodity network flow problem. Additionally, the model requirements stated that each session of flow should remain on a single path. This condition implied that the network flow problem had to be an integer programming problem. Therefore, the network flow programming problem of the model was considered mathematically equivalent to a multi–commodity integer programming problem. The complexity of multi–commodity integer programming problems is NP–hard. A heuristic solving method, Simulated Annealing, was implemented to solve the goal function represented by the network flow programming problem of the model. The findings from this research provide evidence that the implementation of Network Coding in WMNs, nearly doubles the level of the calculated aggregated throughput values. The magnitude of this throughput increase, can be further improved by additional manipulation of the network traffic dispersion. This is achieved by utilising link–state methods, rather than distance vector methods, to establish paths for the sessions of flow, present in the WMNs. / Thesis (M.Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2012.

In this study, the effect of implementing Network Coding on the aggregated throughput in Wireless Mesh Networks, was examined. Wireless Mesh Networks (WMNs) are multiple hop wireless networks, where routing through any node is possible. The implication of this characteristic, is that messages flow across the points where it would have been terminated in conventional wireless networks. User nodes in conventional wireless networks only transmit and receive messages from an Access Point (AP), and discard any messages not intended for them. The result is an increase in the volume of network traffic through the links of WMNs. Additionally, the dense collection of multiple RF signals propagating through a shared wireless medium, contributes to the situation where the links become saturated at levels below their capacity. The need exists to examine methods that will improve the utilisation of the shared wireless medium in WMNs. Network Coding is a coding and decoding technique at the network level of the OSI stack, aimed to improve the boundaries of saturated links. The technique implies that the bandwidth is simultaneously shared amongst separate message flows, by combining these flows at common intermediate nodes. The number of transmissions needed to convey information through the network, is decreased by Network Coding. The result is in an improvement of the aggregated throughput. The research approach followed in this dissertation, includes the development of a model that investigates the aggregated throughput performance of WMNs. The scenario of the model, followed a typical example of indoors WMN implementations. Therefore, the physical environment representation of the network elements, included an indoors log–distance path loss channel model, to account for the different effects such as: power absorption through walls; and shadowing. Network functionality in the model was represented through a network flow programming problem. The problem was concerned with determining the optimal amount of flow represented through the links of the WMN, subject to constraints pertaining to the link capacities and mass balance at each node. The functional requirements of the model stated that multiple concurrent sessions were to be represented. This condition implied that the network flow problem had to be a multi–commodity network flow problem. Additionally, the model requirements stated that each session of flow should remain on a single path. This condition implied that the network flow problem had to be an integer programming problem. Therefore, the network flow programming problem of the model was considered mathematically equivalent to a multi–commodity integer programming problem. The complexity of multi–commodity integer programming problems is NP–hard. A heuristic solving method, Simulated Annealing, was implemented to solve the goal function represented by the network flow programming problem of the model. The findings from this research provide evidence that the implementation of Network Coding in WMNs, nearly doubles the level of the calculated aggregated throughput values. The magnitude of this throughput increase, can be further improved by additional manipulation of the network traffic dispersion. This is achieved by utilising link–state methods, rather than distance vector methods, to establish paths for the sessions of flow, present in the WMNs. / Thesis (M.Ing. (Computer and Electronical Engineering))--North-West University, Potchefstroom Campus, 2012.

The thesis deals with recent problems of waste management in the Czech Republic. In connection with the existing software implementation, the author focuses on the gradual development of advanced mathematical programming models, which generalize existing approaches. The author applies acquired knowledge in the areas of network flows, linear, integer, and stochastic programming. The important role is played by modifications and transformations of the discussed models. They are further used to obtain the experimental results for real-world input data by implementation in GAMS.