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Thesis (M. Phil.)--University of Hong Kong, 2008. / Includes bibliographical references (leaf 109-112) Also available in print.

Paratransit operations in cities in developing countries play an important role in public transport provision. The operations are run within the realm of the infonnal sector and are highly flexible. There are numerous operators running one or two vehicles on a cash basis. This and other issues contribute to the problems with the services that are provided. Poor reliability and stability in supply are the main problems. Despite these serious problems, there has been little research on possible solutions to resolve them. The present study is aimed at improving understanding of the operation of such systems. It assesses the effects on users and operators of different routing, stopping and scheduling regimes. A new model of paratransit operations is developed. The problem of paratransit operations is conceptualised in terms of interactions between demand and supply. The interactions take place in time and geographical space and are shaped by the actions taken by individual users and individual vehicle operators. The model is designed to overcome some of the restrictions on the definitions of time - and in particular space - that are found in existing methodologies. A modelling approach designed to represent the two dimensions as realistically as possible was adopted. Two techniques are central to the construction of the model. Simulation techniques are used to model the temporal processes and a Geographical Information System (GIS) for the spatial processes. The two are complementary to overcome the inherent weaknesses in either approach. Modules are developed to represent demand and supply at a microscopic level. The Model of Paratransit Services (MOPS) involves interfacing a GIS and external modules for dynamic processes. The model was validated against field data collected in Harare, Zimbabwe. Experiments were run for a case study area and the results that were obtained on routing, stopping and scheduling regimes are reported in developing countries.

The thesis addresses a complicated real-world scheduling problem from the space operations environment. The Mars Express Orbiter scheduling problem was first presented as a challenge by the European Space Agency. The thesis compares two different solutions. The first solution is an ad-hoc scheduler that is based on scheduling actions into a set of time windows and heavily utilizes local search techniques. The second solution models the problem as a constraint satisfaction problem (CSP) and uses the SICStus Prolog constraint programming solver to find a solution. Both schedulers are experimentally evaluated and the results are compared. Both approaches were able to provide a working solution. The conclusion however states that the more generic CSP based approach was capable of producing higher quality schedules even without a complicated heuristic. It however to compute the schedule for a small subset of inputs. On the other hand, the ad-hoc scheduler was capable of solving larger inputs but the produced solutions are not as good.

The diploma thesis focuses on the manufacturing order management in company. It contains examples of production systems and their analysis for optimization. During the optimization are monitored major criteria, for example: increase of production rate, resource utilization, and so on. The result of this work is a proposed solutionarising from the outputs of optimization the manufacturing system.

This paper deals with the problem of optimization of a production plan by using genetic algorithms. It contains a brief overview of the principles behind genetic algorithms in scope of evolutionary algorithms and artificial intelligence in general. It also takes a closer look on the challenge of production planning and control and all activities connected to it. This is followed by description of the modification of genetic algorithms that needed to be done in order to implement it into a computer program, which is used to create and optimize the production plan, and is a result to the issue that this paper deals with. Incorporated is detailed escription of principles and functions of the program, that it offers to its users.

Le sujet de thèse porte sur la planification tactique et opérationnelle d’une chaîne logistique dans un contexte dynamique. Nous proposons un modèle de planification basé sur une structure décisionnelle à deux niveaux. Adoptant un processus dynamique permettant d’actualiser les données à chaque étape de planification, le premier niveau planifie la production en recherchant le meilleur compromis entre les leviers décisionnels disponibles liés aux aspects capacité et coût de production. Le deuxième niveau établit un ordonnancement agrégé des opérations de fabrication en minimisant les en-cours. Le recours à une structure décisionnelle intégrée nous a conduit à établir une interaction entre les niveaux supérieur et inférieur de décision, mise en oeuvre par des contraintes dites de conservation d’énergie. Notre approche est modélisée sous la forme d’un problème de satisfaction de contraintes (CSP, Constraint Satisfaction Problem) et évaluée par simulation dans un contexte de données incertaines. Nous avons mené différentes expérimentations portant sur la variation de la demande, la variation de la capacité et la re-planification de la demande. Toutes les expérimentations sont réalisées par deux méthodes de résolution différentes : une méthode basée sur un CSP statique et une méthode basée sur un CSP dynamique. La performance d’une solution de planification/ordonnancement est renseignée par l’ensemble des mesures de la stabilité et de la robustesse. Les expérimentations réalisées offrent une démonstration de la performance de la méthode de résolution basée sur un CSP dynamique par rapport à la méthode statique / This work focuses on the supply chain operational and tactical planning problem in an uncertain environment. We propose a tactical planning model, based on a two-level decisional structure. Adopting a dynamic process, which enables data updating at each planning step, the first level performs a plan by searching for the best compromise between available decision-making levers for production costs and capacity. The second level establishes an aggregate scheduling of production tasks by minimizing the total weighted completion time. The use of an integrated decision structure involves interaction between the upper and lower decision levels constraints, implemented by constraints known as energy conservation constraints. Our approach is formulated according to a constraint satisfaction problem (CSP) and evaluated by simulation under uncertain data. For this, we have developed various experiments related to the variation of customer demand, resource capacity, and the re-planning of demand. All the experiments are carried out by two different methods : a method based on a static CSP and a method based on a dynamic CSP. The performance of a scheduling/planning solution is reported through a set of robustness and stability measurements. Results of experiments confirm the performance of the method based on a dynamic CSP