In this paper, we propose a new model for designing integrated forward/reverse logistics based on pricing policy in direct and indirect sales channel. The proposed model includes producers, disposal center, distributers and final customers. We assumed that the location of final customers is fixed. First, a deterministic mixed integer linear programming model is developed for integrated logistic...

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...

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...

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...

Unit Commitment is a fundamental problem in power systems engineering, deciding which generating units to switch on, and when to switch them on, in order to efficiently meet anticipated demand. It has traditionally been solved as a Mixed Integer Programming (MIP) problem but upcoming changes to the power system drastically increase the MIP solution time. In this paper, we discuss the benefits t...

Mixed Integer Programming (MIP) solvers are highly parameterized and randomized matheuristic algorithms. How to properly design experiments for algorithm comparison using MIP solvers is an important topic. In this work, we analyze the performance variability of MIP solvers due to random seed settings and parameter configurations. The application domain is the vertical flight planning problem (V...

In both industry and the research literature, mixed integer programming (MIP) is often the default approach for solving scheduling problems. In this paper we present and evaluate four MIP formulations for the classical job shop scheduling problem (JSP). While MIP formulations for the JSP have existed since the 1960s, it appears that comprehensive computational studies have not been performed si...

data envelopment analysis (dea) has been widely studied in the literature since its inception with charnes, cooper and rhodes work in 1978. the methodology behind the classical dea method is to determine how much improvements in the outputs (inputs) dimensions is necessary in order to render them efficient. one of the underlying assumptions of this methodology is that the units consume and prod...

A particularly difficult class of scheduling and routing problems involves an objective that is a sum of time-varying action costs, which increases the size and complexity of the problem. Solve-and-improve approaches, which find an initial solution for a simplified model and improve it using a cost function, and Mixed Integer Programming (MIP) are often used for solving such problems. However, ...