Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling

In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the forefront. Nevertheless, the recent pandemic, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects. There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the COVID-19 pandemic has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects

Portfolio Analysis in Supply Chain Management of a Chemicals Complex in Thailand

There is a considerable amount of research literature available for the optimisation of supply chain management of the chemical process industry. The context of supply chain considered in this thesis is the supply chain inside the chemical complex which is the conversion of raw materials into intermediate chemicals and finished chemical products through different chemical processes. Much of the research in the area of planning and scheduling for the process sector has been focused on optimising an individual chemical process within a larger network of a chemicals complex. The objective of this thesis is to develop a multi-objective, multi-period stochastic capacity planning model as a quantitative tool in determining an optimum investment strategy while considering sustainability for an integrated multi-process chemicals complex under future demand uncertainty using the development of inorganic chemicals complex at Bamnet Narong, Thailand as the main case study. Within this thesis, a number of discrete models were developed in phases towards the completion of the final multi-objective optimisation model. The models were formulated as mixed-integer linear programming (MILP) models. The first phase was the development of a multi-period capacity planning optimisation model with a deterministic demand. The model was able to provide an optimal capacity planning strategy for the chemicals complex at Bamnet Narong, Thailand. The numerical results show that based on the model assumptions, all the proposed chemical process plants to be developed in the chemicals complex are financially viable when the planning horizon is more than 8 years. The second phase was to build a multi-period stochastic capacity planning optimisation model under demand uncertainty. A three-stage stochastic programming approach was incorporated into the deterministic model developed in the first phase to capture the uncertainty in demand of different chemical products throughout the planning horizon. The expected net present value (eNPV) was used as the performance measure. The results show that the model is highly demand driven. The third phase was to provide an alternative demand forecasting method for capacity planning problem under demand uncertainty. In the real-world, the annual increases in demand will not be constant. A statistical analysis method named “Bootstrapping” was used as a demand generator for the optimisation model. The method uses historical data to create values for the future demands. Numerical results show that the bootstrap demand forecasting method provides a more optimistic solution. The fourth phase was to incorporate financial risk analysis as constraints to the previously developed multi-period three-stage stochastic capacity planning optimisation model. The risks associated with the different demand forecasting methods were analysed. The financial risk measures considered in this phase were the expected downside risk (EDR) and the mean absolute deviation (MAD). Furthermore, as the eNPV has been used as the usual financial performance measure, a decisionmaking method, named “Minimax Regret” was applied as part of the objective function to provide an alternative performance measure to the developed models. Minimax Regret is one kind of decision-making theory, which involves minimisation of the difference between the perfect information case and the robust case. The results show that the capacity planning strategies for both cases are identical Finally, the last phase was the development of a multi-objective, multi-period three stage stochastic capacity planning model aiming towards sustainability. Multiobjective optimisation allows the investment criteria to be traded off against an environmental impact measure. The model values the environmental factor as one of the objectives for the optimisation instead of this only being a regulatory constraint. The expected carbon dioxide emissions was used as the environmental impact indicator. Both direct and indirect emissions of each chemical process in the chemicals complex were considered. From the results, the decision-makers will be able to decide the most appropriate strategy for the capacity planning of the chemicals complex

Products and Services

Today’s global economy offers more opportunities, but is also more complex and competitive than ever before. This fact leads to a wide range of research activity in different fields of interest, especially in the so-called high-tech sectors. This book is a result of widespread research and development activity from many researchers worldwide, covering the aspects of development activities in general, as well as various aspects of the practical application of knowledge

New Technologies in the Oil and Gas Industry

Oil and gas are the most important non-renewable sources of energy. Exploring, producing and managing these resources in compliance with HSE standards are challenging tasks. New technologies, workflows and procedures have to be implemented.This book deals with some of these themes and describes some of the advanced technologies related to the oil and gas industry from HSE to field management issues. Some new technologies for geo-modeling, transient well testing and digital rock physics are also introduced. There are many more technical topics to be addressed in future books. This book is aimed at researchers, petroleum engineers, geoscientists and people working within the petroleum industry