of that test. Furthermore, new resources may be installed or purchased, if needed, during the course of the testing. In this work we propose a new scheduling MILP model that addresses three issues. More specifically, the model (i) handles resource allocation as a decision variable with the possibility

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Abstract This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

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

) 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

by means of piecewise-linear functions, so that UC can be approximated by a Mixed-Integer Linear Program (MILP); applying the available efficient general-purpose MILP solvers to the resulting formulations, good quality solutions can be obtained in a relatively short amount of time. We build

that general disjunctions can provide speed improvements for hard MILP models. The speed-up is due to new and efficient ways to (i) trigger the inclusion of a general disjunction only when it is likely to be beneficial, and (ii) construct effective general disjunctions very quickly. Our empirical results show

This paper addresses the problem of automatically determining the optimal economic retrofit of heat exchanger networks. It is a rigorous MILP (Mixed Integer Linear Programming) approach that considers rearrangement of the existing heat exchanger units, heat transfer area addition and new exchanger

In this paper, we deal with the separation of data by concurrently determined, piecewise nonlinear discriminant functions. Toward the end, we develop a new l1-distance norm error metric and cast the problem as a mixed 0-1 integer and linear programming (MILP) model. Given a finite number

This paper presents a new multiple time grid continuous time MILP model for the short-term scheduling of multistage, multiproduct plants. It can handle both release and due dates and different objective functions efficiently, such as the minimization of total cost, total earliness or makespan