METHODS AND MATHEMATICAL MODELS FOR THE OPTIMIZATION IN LOGISTICS AND PRODUCTION

This dissertation extensively describes the activities carried out during the Ph.D.. With particular regard to the manufacturing industry, it is widely known the key role covered by the Operations Management. In brief, it assures that business operations are efficient in terms of using as few resources as needed, and effective in terms of meeting customer demand. With the aim of providing practitioners with innovative operating tools, the research activity carried out focuses on the development of methods and mathematical models approaching several questions within logistics, production management, and maintenance. When the problem can be faced analytically, i.e., mathematically, the approach is able to give an optimal, or quasi-optimal, solution. The objective of this research is thus to provide a significant contribution to extending the toolbox available to all practitioners in the manufacturing industry, useful to find optimal or heuristic solutions, and to investigate several issues within the Operations Management area. The work done concretized in: (i) five models related to maintenance, (ii) five models concerning production management, and (iii) twelve models dealing with logistic issues. The models and the approaches were developed exploiting several advanced techniques: Artificial Intelligence, Markov Processes, Multivariate Statistics, and Simulation. Since the issues related to Operations Management are still growing, future work may be thus devoted to further extending the research here presented.