The number of novel applications of multi-agent systems has followed an exponential trend over the last few years, ranging from online auction design, through in multi-sensor networks, to scheduling of tasks in multi-actor systems. Multi-agent systems designed for all these applications generally require some form of optimisation in order to achieve their goal. This tutorial will present state of the art solution techniques for optimisation problems in different areas of multi-agent systems, particularly focusing on market based resource allocation, coalition formation and cooperative decentralised decision making. Moreover, open questionsand promising future research directions will be highlighted. The potential targets are PhD students and researchers who have a basic background on AI techniques for optimisation and are interested in the field of Multi-Agent Systems, or conversely that have been working on multi-agent systems and want to learn more about optimisation techniques that could be applied in this field.