We propose a general-purpose heuristic approach combining metaheuristics and Mixed Integer Programming to find high quality solutions to the challenging singleand parallel-machine capacitated lotsizing and scheduling problem with sequence-dependent setup times and costs. Commercial solvers fail to solve even medium-sized instances of this NP-hard problem, therefore heuristics are required to fi...

We present a parallel local search approach for obtaining high quality solutions to the Fixed Charge Multicommodity Network Flow problem (FCMNF). The approach proceeds by improving a given feasible solution by solving restricted instances of the problem where flows of certain commodities are fixed to those in the solution while the other commodities are locally optimized. We derive multiple ind...

and Company LLC (GMO) uses mixed-integer-programming (MIP) methods to construct portfolios that are close (in terms of sector and security exposure) to target portfolios, have the same liquidity, turnover, and expected return as the target portfolios, control frictional costs, and do so with fewer distinct stocks and with fewer transactions. It also applies MIP methods to portfolios consisting ...

s: A framework for incorporating uncertainty in water distribution models that uses generalised likelihood unbiased estimation (GLUE) and mixed-integer programming (MIP) is proposed and applied to a small water distribution system. Model parameters with uncertainty are first modelled in GLUEWIN and the mean estimates are used instead of single-point estimates. The MIP is solved in GAMS using CP...

Abstract Despite their great success in recent years, neural networks have been found to be vulnerable adversarial attacks. These attacks are often based on slight perturbations of given inputs that cause them misclassified. Several methods proposed formally prove robustness a network against such However, these typically give rise high computational demands, which severely limit scalability. R...

We present new families of valid inequalities for (mixed) integer programming (MIP) problems. These valid inequalities are based on a generalization of the 2-step mixed integer rounding (MIR), proposed by Dash and Günlük (2006). We prove that for any positive integer n, n facets of a certain (n + 1)-dimensional mixed integer set can be obtained through a process which includes n consecutive app...

Mixed-integer conic programming is a generalization of mixed-integer linear programming. In this paper, we present an extension of the duality theory for mixed-integer linear programming (see [4], [11]) to the case of mixed-integer conic programming. In particular, we construct a subadditive dual for mixed-integer conic programming problems. Under a simple condition on the primal problem, we ar...

Good inventory management is essential for a firm to be cost competitive and to acquire decent profit in the market, and how to achieve an outstanding inventory management has been a popular topic in both the academic field and in real practice for decades. As the production environment getting increasingly complex, various kinds of mathematical models have been developed, such as linear progra...

The Aircraft Landing Problem consists in sequencing aircraft on the available runways and scheduling their landing times taking into consideration several operational constraints, order to increase runway capacity and/or reduce delays. In this work we propose a new Mixed Integer Programming (MIP) model for landings single or multiple independent incorporating safety constraints by means of sepa...

This paper considers the single-machine problem with job release times and flexible preventive maintenance activities to minimize total weighted tardiness, a complicated scheduling for which many algorithms have been proposed in literature. However, considered problems are rarely solved by genetic (GAs), even though it has successfully various combinatorial optimization problems. For problem, w...