depots and the corresponding consumer markets that receive large amounts of gasoline, diesel, LPG and aviation fuel. An MILP optimization model that is based on a convex-hull formulation is proposed for the scheduling system. The model must satisfy all the operational constraints, such as mass balances

The goal of this paper is to develop models and methods that use complementary strengths of Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) techniques to solve problems that are otherwise intractable if solved using either of the two methods. The class of problems considered

) shedding loads and (iii) switching generators, while maximizing load supply. A key feature of the new method is that network constraints are explicitly included in the MILP problem, resulting in balanced, steadystate feasible DC solutions. A subsequent AC optimal load shedding optimization on the islanded

This works optimizes a heating system including demand side management within two of EPFL’s buildings. It combines building simulation with linear optimization providing results at low computational efforts. Overall economies of up 20 % are possible, when the buildings are used as a thermal energy

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that contributes to base-load energy. Finally, an optimization model is developed to find the optimal size of hydrogen production plants to be developed in different zones, as well as optimal hydrogen transportation routes to achieve a feasible hydrogen economy penetration in Ontario up to 2025. The proposed model

of the products, testing may last up to 15 years, and the scheduling of tests should be made with the goal of minimizing the time to market and the cost of the testing. The various optimization models that have been proposed consider a set of candidate products for which the cost, duration and resource

CAD-systems supporting hardware/software codesign map different tasks of an algorithm onto processors. Some of the processors are programmable and others are application specific. We propose a new MILP (mixed integer linear program) model that allows to determine a mapping optimizing a trade off

than standard MILP methods, and require less computational effort. Index Terms—Hybrid systems, mathematical optimization, mixed-integer linear programming (MILP), obstacle avoidance, path and trajectory planning, robot motion planning, trajectory generation. I.

This paper focuses on optimal path planning for vehicles in known environments. Previous work has presented mixed integer linear programming (MILP) formulations, which suffer from scalability issues as the number of obstacles, and hence the number of integer variables, increases. In order