Solving mixed integer linear programming (MILP) problems is a difficult task due to the parallel use of both integer and non-integer values. One of the most widely used solution is to solve the problem in the real space and they apply additional iteration steps (so-called cutting-plane algorithms or Gomory’s cuts) to narrow down the solution to the optimal integer solution. The ABS class of alg...

This paper investigates the problem of selecting and scheduling a set of projects among available projects. Each project consists of several tasks and to perform each one some resource is required. The objective is to maximize total benefit. The paper constructs a mathematical formulation in form of mixed integer linear programming model. Three effective metaheuristics in form of the imperialis...

Cloud computing – running large-scale computationand data-intensive services on inexpensive onthe-fly clusters – has become increasingly popular in recent years due to the advent of MapReduce and similar large-scale data parallel systems. Cloud provisioning, i.e., allocating resources for cluster requests, is the first step toward instantiating such clusters. In this report, we formally define ...

This article discusses solving non-linear programming problems containing integer, discrete and continuous variables. A novel mixed integer-discrete-continuous, non-linear optimization method based on Differential Evolution algorithm is described. Also the required handling techniques for integer, discrete and continuous variables are described including the techniques needed to handle boundary...

This paper studies the hybrid flow shop scheduling where the optimization criterion is the minimization of total tardiness. First, the problem is formulated as a mixed integer linear programming model. Then, to solve large problem sizes, an artificial immune algorithm hybridized with a simple local search in form of simulated annealing is proposed. Two experiments are carried out to evaluate th...

In this work we focus on solving quadratically constrained pseudoboolean optimization problems with quadratic objective as mixed integer linear programs. The standard mixed integer linear formulation of such problems is strengthened using valid inequalities derived from solving Reformulation-Linearization relaxation called partial DRL* relaxation. The proposed PDRL* relaxation features block-de...

 We consider a generalization of the classical quadratic assignment problem, where coordinates of locations are uncertain and only upper and lower bounds are known for each coordinate. We develop a mixed integer linear programming model as a robust counterpart of the proposed uncertain model. A key challenge is that, since the uncertain model involves nonlinear objective function of the ...

Although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. This paper deals with scheduling jobs in lot streaming flexible flow line problems. The paper mathematically formulates the problem by a mixed integer linear programming model. This model solves small instances to optimality. Moreo...