Decision support or operations research has been a hybrid discipline whose development has always been very closely linked to information technology and communication (ICT). It refers to combinatorial and continuous optimisation, optimal control, multi-criteria modelling, scheduling, planning and POAG, game theory, performance evaluation, supervised learning, network optimisation and processes at the methodology level.
Operations research was first related to centralised organisational design and mainframe simulation and optimisation software. But in the internet era, smartphones and internet of things, the emergence of new services and socio-economic changes motivate operations researchers to confront new types of problems (e.g. revenue management, pricing, smart grids, consideration of uncertainties, the notion of robustness, average complexity, etc.), new decision paradigms (e.g. collaboration, online, dynamic, etc.) and new contextual developments (e.g. very large data size, big data, cloud architectures, generic requirements).
In this context, particular topics will be very significant in the future:
- The integration of models and techniques of operations research in contexts of dynamic data acquisition, communication and collaborative/dynamic decision making. This applies to both the support of the decentralisation process (even outsourcing) within companies, services and organisations, and the rise of technology monitoring and data management in real time, geo-location, and mobile communication.
- The integration into models of emerging societal concerns related to the preservation of the environment, mobility management and energy issues.
- The generic aspects and the integration and decomposition schemes of algorithms for operations research.
- Stochastic and uncertainty issues. These problems are all the more acute according to the number of applications of operations research which concern the control of dynamic systems operating in a not completely predictable environment.
- Evaluation of algorithms and problems (e.g. complexity analysis, approximation theory) with or without probabilistic sense.
- The adaptation of standard algorithms to very large data sizes (so-called big data) (e.g. social networks, dynamic graphs, internet or network mobility).
Suitable topics include, but are not limited to, the following:
- New operations research methodologies to build innovative systems in SMEs
- Collaborative heuristics for project management
- Machine learning techniques to support innovation in monitoring services
- Fuzzy-based decision support systems to impact on knowledge-based economy
- Operations research-based applications and new challenging domains in supply chain management, revenue management, mobility management, vehicle sharing and dynamical system monitoring
- Generic mathematical programming and constraint programming solutions for complex decision problems
- Fast prototyping for complex combinatorial optimisation applications
- Operations research applications involving large scale data and HPC architectures
- Applications of game theory to economical decision making
- Issues in comparison of innovation systems to create new systems over multiple problem domains (e.g. internet of things)
- Analytical and stochastic modelling techniques for dynamical systems
Submission of manuscripts: 15 March, 2014
Feedback to authors: 15 April, 2014
Submission for second review: 1 May, 2014
Notification of final acceptance: 30 May, 2014