MOVES: Efficient and Sustainable Mobility Management (2013-2015)

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TIN2011-28336 - Project funded by Ministry of Science and Innovation (Spain)

Mobility Management is becoming an important issue for multinational companies, as well as for the local authorities of large cities. Among other issues, Management Mobility attempts to reduce the average time of workers for transportation to the workplace. The reduction in commuting time improves the quality of life, reduces costs, and diminishes environmental impact. In the end, it results in less traffic and less congested cities. To achieve this reduction in travel times, it is necessary to propose solutions that take into account, for instance, workplace location changes, employee assignments, openings of new transport lines, etc. The problems to be solved are quite complex. They are usually NP-hard combinatorial optimization problems. There are also many alternatives and constraints, such as schedules, compatibility, work groups, public transport routes , etc...


The project Efficient and Sustainable Mobility Management (MOVES from now on), intends to address these issues by developing optimization models based on meta-heuristic techniques, which are characterized by exploring the search space efficiently. To obtain these models, we must take into account three main factors.  First, the treatment of multiple constraints that are given by the people, the city, the companies, etc. Second, the optimization of different objectives or different costs (environmental, social, and economic) that might be conflicting with each other, i.e. one can be optimized to the detriment of others. And finally, another important aspect of decision making is to build models that do not provide a single solution but a set of solutions, all of them valid or equivalent, so that the manager can choose from. Or, to obtain solutions that are robust to changes in working conditions  and easily adaptable.


In short, this proposal is aimed at research and innovation in models based on meta-heuristics for optimal management of mobility, that address the three aspects mentioned above. The studied models will be validated with data from real cases provided by companies in order to quantify the gains in terms of travel time, cost and quality of the solutions offered.