In this paper, we present an analysis of the strength of sparse cutting-planes for mixed integer linear programs (MILP) with sparse formulations. We examine three kinds of problems: packing problems, covering problems, and more general MILPs with the only assumption that the objective function is non-negative. Given a MILP instance of one of these three types, assume that we decide on the suppo...

Modularity density maximization is a clustering method that improves some issues of the commonly-used modularity maximization approach. Recently, some Mixed-Integer Linear Programming (MILP) reformulations have been proposed in the literature for the modularity density maximization problem, but they require as input the solution of a set of auxiliary binary Non-Linear Programs (NLPs). These can...

The Monash Interview for Liaison Psychiatry (MILP) is a structured interview designed for use with patients who have physical and psychiatric comorbidity. Linked to a computerized diagnostic algorithm, the MILP is able to establish diagnoses according to DSM-III-R, International Classification of Diseases--10th Edition (ICD-10), and DSM-IV criteria, as well as a range of other criteria relevant...

This paper presents a new formulation for intentional controlled islanding (ICI) of power transmission grids based on mixed-integer linear programming (MILP) DC optimal flow (OPF) model. We highlight several deficiencies the most well-known this problem and propose enhancements their improvement. In particular, we alternative optimization objective that may be more suitable ICI than minimizatio...

In this paper, we present an efficient strategic/tactical planning model for offshore oilfield development problem that is fairly generic and can be extended to include other complexities. The proposed multiperiod non-convex MINLP model for multi-field site includes three components (oil, water and gas) explicitly in the formulation using 3 rd and higher order polynomials avoiding bilinear and ...

Production planning for biopharmaceutical portfolios becomes more complex when products switch between fed-batch and continuous perfusion culture processes. This article describes the development of a discrete-time mixed integer linear programming (MILP) model to optimize capacity plans for multiple biopharmaceutical products, with either batch or perfusion bioprocesses, across multiple facilit...

The design and operations of energy systems are key issues for matching energy supply and consumption. Several optimization methods based on the mixed integer linear programming (MILP) have been developed for this purpose. However, due to uncertainty of some parameters like market conditions and resource availability, analyzing only one optimal solution with mono objective function is not su ci...

This paper presents a sound and complete fault detection approach for cyber-physical systems represented by hidden-mode switched affine models with time varying parametric uncertainty. The fault detection approach builds upon techniques from model invalidation. In particular, a set-membership approach is taken where the noisy input-output data is compared to the set of behaviors of a nominal mo...

The profound transformation of large-scale Industrial Control Systems (ICS), e.g., smart energy networks (Smart Grids), from a proprietary and isolated environment to a modern architecture brings several new challenges. Nowadays, ICS network designers need to accommodate a variety of devices and communication media/protocols with industry-specific requirements pertaining to real-time delivery o...

The management of complex energy systems where different power sources are active in a time varying scenario of costs and prices needs efficient optimization approaches. Usually the scheduling problem is is formulated as a Mixed Integer Linear Programming (MILP) to guarantee the convergence to the global optimum. The goal of this work is to propose and compare a hybrid technique based on Artifi...