- Design of Reverse Supply Chains in the context of the development of circular economy, by Zoé Krug, ISAE-SUPAERO, Toulouse
In order to respond to current environmental, economic and social challenges, many institutional actors promote the design of Reverse Supply Chains (RSC). These ones particularly allow to minimize waste and maximize savings in raw materials. Two main difficulties appear when designing such systems. The first one is the presence of many factors of uncertainty in the decision making process. The second one is the simultaneous consideration of economic, environmental and social objectives in order to enable the sustainability of the created RSC. In this context, firstly, we provide methodological tools based on new models for taking into account uncertainty. We particularly propose two criteria ($R_*$ and $LexiR_*$) which make it possible to differentiate areas of risk and opportunity where the attitude of the decision-maker will not be considered in the same way. We compare these new criteria with classic criteria from the literature through extended numerical experiments and we show that they make it possible to explore new opportunities, while keeping control over the level of taken risk. Secondly, we propose new multi-objectives optimization models taking into account the three objectives of sustainable development simultaneously. We highlight the existence of many compromise solutions, allowing the decision-maker to choose the solution that is the most suitable for him/her according to his/her priorities. Finally, we propose a study of the concept of social and environmental equity between different locations where the RSC is implemented.
- Threshold robustness in the drilling rig routing problem, by Igor Kulachenko, Novosibirsk State University
We consider the real-world Drilling Rig Routing Problem (DRRP) in an uncertain environment. There is a set of customers that are exploration sites requiring well-drilling work. For each customer, we know the number of wells that need to be drilled within a given time interval, and it is allowed to partition the set of wells so that several drilling rigs perform the required work. In the real world, unforeseen circumstances can affect drilling time, and that, if disregarded, can lead to a disruption of the work plan. Thus, in this problem, we maximize the norm of deviations of drilling times from expected values when there is still a set of routes and schedules for a fleet of drilling rigs to perform all well-drilling requests in time with total traveling costs no more than a given threshold. It is a so-called threshold robustness approach. In the talk, we will present an integer linear programming model for the DRRP with uncertainties as well as some preliminary results on developing a metaheuristic algorithm for the problem.