Abstract: There is provided a computer-implemented method for controlling operation of a plurality of devices of a facility that consume energy. The method comprises obtaining parameters of an energy model representing the energy consumed by the plurality of devices of the facility, the energy model including a first plurality of variables for operating the plurality of devices and a second plurality of variables for scheduling activities to be conducted in the facility; receiving requests for the activities to be conducted in the facility, the requests including requirements in relation to the activities; and automatically determining, based on the energy model, values of the first plurality of variables to control the operation of the plurality of devices, and values of the second plurality of variables that meet the requirements in relation to the activities.

Abstract: An alternating current (AC) power flow analysis in an electrical power network. Based on information relating to buses and transmission lines connecting the buses in the electrical power network, a convex approximation of AC power flows in the electrical power network is determined. The convex approximation of the AC power flows comprises convex approximation of nonlinear cosine terms associated with active power components and reactive power components of the AC power flows. A convex objective function associated with the electrical power network is optimised using the convex approximation of the AC power flows.

Abstract: With rapid population growth and urbanization, emergency services in various cities around the world worry that the current transportation infrastructure is no longer adequate for large-scale evacuations. This disclosure considers how to mitigate this issue through infrastructure upgrades, such as the additions of lanes to road segments and the raising of bridges and roads. This disclosure proposes a MIP model for deciding the most effective infrastructure upgrades as well as a Benders decomposition approach where the master problem jointly plans the upgrades and evacuation routes and the subproblem schedules the evacuation itself.

Abstract: This disclosure considers a vehicle routing problem with pickup and delivery, time windows, and location resource constraints. Locations provide a number of cumulative resources that are utilized by vehicles either during service (e.g., forklifts) or for the entirety of their visit (e.g., parking bays). The problem is highly challenging from a computational standpoint as the resource constraints add temporal dependencies between vehicles and a scheduling substructure not featured in traditional vehicle routing problems. The main contribution of this disclosure is a branch-and-price-and-check model that incorporates a branch-and-price algorithm that solves the underlying vehicle routing problem, and a constraint programming subproblem that checks the feasibility of the location resource constraints, and then adds combinatorial nogood cuts to the master problem if the resource constraints are violated.

Abstract: There is provided a computer-implemented method for controlling operation of a plurality of devices of a facility that consume energy. The method comprises obtaining parameters of an energy model representing the energy consumed by the plurality of devices of the facility, the energy model including a first plurality of variables for operating the plurality of devices and a second plurality of variables for scheduling activities to be conducted in the facility; receiving requests for the activities to be conducted in the facility, the requests including requirements in relation to the activities; and automatically determining, based on the energy model, values of the first plurality of variables to control the operation of the plurality of devices, and values of the second plurality of variables that meet the requirements in relation to the activities.

Abstract: This disclosure relates to planning movement of multiple groups over a transport network, for example, but not limited to, the evacuation of persons from geographical zones. A processor receives an initial set of paths for the multiple groups to move through the transport network to respective arrival locations and for each group an initial path to the respective arrival location and an initial departure schedule. The processor then determines based on the initial departure schedules and initial paths one or more critical groups that violate a movement performance threshold and further determines based on the transport network an updated set of paths by adding one or more paths for each critical group to the initial set of paths. Finally, the processor determines for each group an updated path to the arrival location and an updated departure schedule based on the updated set of paths.

Abstract: An alternating current (AC) power flow analysis in an electrical power network. Based on information relating to buses and transmission lines connecting the buses in the electrical power network, a convex approximation of AC power flows in the electrical power network is determined. The convex approximation of the AC power flows comprises convex approximation of nonlinear cosine terms associated with active power components and reactive power components of the AC power flows. A convex objective function associated with the electrical power network is optimised using the convex approximation of the AC power flows.

Abstract: In one exemplary embodiment of the invention, a method includes: receiving, by an input, input data descriptive of a stochastic scheduling optimization problem; generating, by a processor, at least one solution to the stochastic scheduling optimization problem using a one-step anticipatory algorithm, where the one-step anticipatory algorithm is configured to reduce an anticipatory gap of the stochastic scheduling optimization problem, where the anticipatory gap is a measure of stochasticity of the stochastic scheduling optimization problem, where the one-step anticipatory algorithm operates by determining a set of possible decisions for the stochastic scheduling optimization problem, generating a plurality of scenarios and solving the plurality of scenarios to obtain the at least one solution; and outputting, by an output, the generated at least one solution.

Abstract: In one exemplary embodiment, a method includes: modeling, by at least one processor, a problem as an approximated exogenous Markov decision process (X-MDP); converting, by the at least one processor, the approximated X-MDP into a Markov decision process (MDP); solving, by the at least one processor, the MDP using at least one search algorithm to obtain a decision; and returning, by the at least one processor, the decision.

Abstract: In one exemplary embodiment of the invention, a method includes: receiving, by an input, input data descriptive of a stochastic scheduling optimization problem; generating, by a processor, at least one solution to the stochastic scheduling optimization problem using a one-step anticipatory algorithm, where the one-step anticipatory algorithm is configured to reduce an anticipatory gap of the stochastic scheduling optimization problem, where the anticipatory gap is a measure of stochasticity of the stochastic scheduling optimization problem, where the one-step anticipatory algorithm operates by determining a set of possible decisions for the stochastic scheduling optimization problem, generating a plurality of scenarios and solving the plurality of scenarios to obtain the at least one solution; and outputting, by an output, the generated at least one solution.