Solving hyperelastic problems using mixed LSFEM

Solving zero-one mixed integer programming problems using tabu search

We describe a tabu search (TS) approach for solving general zero-one mixed integer programming (MIP) problems that exploits the extreme point property of zero-one solutions. Specialized choice rules and aspiration criteria are identified for the problems, expressed as functions of integer infeasibility measures and objective function values. The first-level TS mechanisms are then extended with ...

Solving Mixed-Integer Programming Problems Using Piecewise Linearization Methods

We present an overview on piecewise linearization methods for MINLPs. This will include the concept of disjunctive constraints, which is necessary to define logarithmic reformulations of the so called disaggregated convex combination method and the convex combination method. For the case of a general univariate quadratic function we also calculate the linearization error and proof that equidist...

Solving Mixed Integer Bilinear Problems Using MILP Formulations

In this paper, we examine a mixed integer linear programming (MILP) reformulation for mixed integer bilinear problems where each bilinear term involves the product of a nonnegative integer variable and a nonnegative continuous variable. This reformulation is obtained by first replacing a general integer variable with its binary expansion and then using McCormick envelopes to linearize the resul...

Solving Multistage Mixed Nonlinear Convex Stochastic Problems

We present an algorithm to solve multistage stochastic convex problems, whose objective function and constraints are nonlinear. It is based on the twin-node-family concept involved in the Branch-and-Fix Coordination method. These problems have 0–1 mixed-integer and continuous variables in all the stages. The non-anticipativity constraints are satisfied bymeans of the twin-nodefamily strategy. I...

Solving Uncertain Problems using ANFIS