We present a multi-objective two-echelon vehicle routing problem with vehicle synchronization and "grey zone" customers arising in the context of urban freight deliveries. Inner-city center deliveries are performed by small vehicles due to access restrictions, while deliveries outside this area are carried out by conventional vehicles for economic reasons. Goods are transferred from the first to the second echelon by synchronized meetings between vehicles of the respective echelons. We investigate the assignment of customers to vehicles, i.e., to the first or second echelon, within a so-called "grey Zone" on the border of the inner city and the area around it. While doing this, the economic objective as well as negative external effects of transport, such as emissions and disturbance (negative impact on citizens due to noise and congestion), are taken into account to include objectives of companies as well as of citizens and municipal authorities. Our metaheuristic - a large neighborhood search embedded in a heuristic rectangle/cuboid splitting - addresses this problem efficiently. We investigate the impact of the free assignment of part of the customers ("grey Zone") to echelons and of three different city layouts on the solution. Computational results show that the impact of a "grey Zone" and thus the assignment of these customers to echelons depend significantly on the layout of a city. Potentially pareto-optimal solutions for two and three objectives are illustrated to efficiently support decision makers in sustainable city logistics planning processes.

The operational scheduling at coal handling facilities is of the utmost importance to ensure that the coal consuming processes are supplied with a constant feed of good quality coal. Although the Sasol Coal Handling Facility (CHF) were not designed to perform coal blending during the coal handling process, CHF has to blend the different sources to ensure that the quality of the feed supplied is of a stable nature. As a result, the operation of the plant has become an extremely complex process. Consequently, human intelligence is no longer sufficient to perform coal handling scheduling and therefore a scheduling model is required to ensure optimal plant operation and optimal downstream process performance. After various attempts to solve the scheduling model optimally, i.e. with exact solution methods, it was found that it is not possible to accurately model the complexities of CHF in such a way that the currently available exact solvers can solve it in an acceptable operational time. Various alternative solution approaches are compared, in terms of solution quality and execution speed, using a simplified version of the CHF scheduling problem. This investigation indicates that the Simulated Annealing (SA) metaheuristic is the most efficient solution method to provide approximate solutions. The metaheuristic solution approach allows one to model the typical sequential thoughts of a control room operator and sequential operating procedures. Thus far, these sequential rules could not be modelled in the simultaneous equation environment required for exact solution methods. An SA metaheuristic is developed to solve the practical scheduling model. A novel SA approach is applied where, instead of the actual solution being used for neighbourhood solution representation, the neighbours are indirectly represented by the rules used to generate neighbourhood solutions. It is also found that the initial temperature should not be a fixed value, but should be a multiple of the objective function value of the initial solution. An inverse arctan-based cooling schedule function outperforms traditional cooling schedules as it provides the required diversification and intensification behaviour of the SA. The scheduling model solves within 45 seconds and provides good, practically executable results. The metaheuristic approach to scheduling is therefore successful as the plant complexities and intricate operational philosophies can be accurately modelled using the sequential nature of programming languages and provides good approximate optimal solutions in a short solution time. Tests done with live CHF data indicate that the metaheuristic solution outperforms the current scheduling methodologies applied in the business. The implementation of the scheduler will lead to a more stable factory feed, which will increase production yields and therefore increase company profits. By reducing the amount of coal re-handling (in terms of throw-outs and load-backs at mine bunkers), the scheduler will reduce the coal handling facility’s annual operating cost by approximately R4.6 million (ZAR). Furthermore, the approaches discussed in this document can be applied to any continuous product scheduling environment. Additional information available on a CD stored at Level 3 of the Merensky Library. / Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2011. / Industrial and Systems Engineering / unrestricted

The thesis deals with investment decision making. It starts from the decision making situation about the making of an investment portfolio of the open unit trusts. The whole decision making process is described, namely the methodical approaches used in terms of the portfolio making procedure. Thus, the main part of this paper focuses on a detailed description of an algorithm of the fuzzy weight estimation method, fuzzy multiple criteria evaluation method and fuzzy multiple objective programming method. The methods are proposed on the basis of current concepts; they conclude the new ideas as well. The fuzzy weight estimation method is able to calculate the weights of criteria according to their linguistically expressed importance. The fuzzy multiple criteria evaluation method accepts uncertain input data in the form of the fuzzy numbers. The alternatives are evaluated by the concept of the preference relations. This method provides a division of the alternatives into the effective and ineffective. The fuzzy multiple objective programming method also works with the uncertain elements as fuzzy numbers. To solve the particular mathematical models, the Bellman's optimality approach is applied. The method is proposed in the interactive form. The decision maker can change a current solution by his/her additional (vague) preferences. The proposed concepts form the two-phase decision making procedure that is applied in the practical situation of the portfolio making in the field of the capital market with open unit trusts offered by the Česká spořitelna investment company. Two types of investors are defined, the investment situations are described, and the results are analyzed in detail. The decision making theory, the fuzzy sets theory and the capital market of collective investment, or with unit trusts, are introduced in a necessary scope. The instigation of my dissertation is to solve the real decision making situation. The investment decision making process is described and the methodical approaches are proposed in order to make the portfolio of unit trusts.