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...

In this paper recently developed mixed-integer programming (MIP) tools to the problem of optimal siting and sizing of distributed generators in a distribution network. Here three methodologies for solving the DGPP via mixed-integer linear programming (MILP) and mixed-integer nonlinear programming (MINLP) approaches are compared. The single MILP approach uses the well-known DC linear approximati...

We consider the application of mixed-integer linear programming (MILP) solvers to the minimization of submodular functions. We evaluate common large-scale linear-programming (LP) techniques (e.g., column generation, row generation, dual stabilization) for solving a LP reformulation of the submodular minimization (SM) problem. We present heuristics based on the LP framework and a MILP solver. We...

We first introduce a novel modeling framework, called linear coupled component automata (LCCA), to facilitate the modeling of discrete-continuous dynamical systems with piecewise constant derivatives. Second, we provide a procedure for transforming models in this framework to mixed-integer linear programming (MILP) constraints. Traditionally, such systems have been modeled directly with MILP co...

This short communication presents a generic mathematical programming formulation for Computer-Aided Molecular Design (CAMD). A given CAMD problem, based on target properties, is formulated as a Mixed Integer Linear/Non-Linear Program (MILP/MINLP). The mathematical programming model presented here, which is formulated as an MILP/MINLP problem, considers first-order and second-order molecular gro...

Mixed logical linear programming MLLP is an extension of mixed integer linear pro gramming MILP It can represents the discrete elements of a problem with logical propo sitions and provides a more natural modeling framework than MILP It can also have computational advantages partly because it eliminates integer variables when they serve no purpose provides alternatives to the traditional continu...

The aim of this study is to propose a new mixed integer linear programming (MILP) model to find the minimum required number of yard cranes, Rubber tyred gantry cranes (RTGCs), for completion the total amount of works at the end of planning horizon. In other word, we find the optimal number of yard cranes in a container terminal which completes the total amount of works. The paper supports the p...

We reformulate branch-and-bound feature selection employing L1 or particular Lp metrics, as mixed-integer linear programming (MILP) problems, affording convenience of widely available MILP solvers. These formulations offer direct influence over individual pairwise interclass margins, which is useful for feature selection in multiclass settings.

In this paper, a hybrid multi-criteria decision-making (MCDM)-method and mixed integer linear programming (MILP) approach in order to evaluation of the returned products' collectors along with their ordered quantities, is utilized. Firstly, the most important criteria of collection center in the car industry are identified. Then, in order to evaluate these proposed criteria, a hybrid Fuzzy Deci...

Branch-and-Bound (B&B) is perhaps the most fundamental algorithm for the global solution of convex Mixed-Integer Nonlinear Programming (MINLP) problems. It is well-known that carrying out branching in a non-simplistic manner can greatly enhance the practicality of B&B in the context of Mixed-Integer Linear Programming (MILP). No detailed study of branching has heretofore been carried out for MI...