Parallel graph partitioning is a difficult issue, because the best sequential graph partitioning methods known to date are based on iterative local optimization algorithms that do not parallelize nor scale well. On the other hand, evolutionary algorithms are highly parallel and scalable, but converge very slowly as problem size increases. This paper presents methods that can be used to reduce p...

in this paper, a novel mathematical model for a preemption multi-mode multi-objective resource-constrained project scheduling problem with distinct due dates and positive and negative cash flows is presented. although optimization of bi-objective problems with due dates is an essential feature of real projects, little effort has been made in studying the p-mmrcpsp while due dates are included i...

distribution centers (dcs) play important role in maintaining the uninterrupted flow of goods and materials between the manufacturers and their customers.this paper proposes a mathematical model as the bi-objective capacitated multi-vehicle allocation of customers to distribution centers. an evolutionary algorithm named non-dominated sorting ant colony optimization (nsaco) is used as the optimi...

Dafo, a multi-agent framework dedicated to distributed coevolutionary genetic algorithms (CGAs) is used to evaluate dLCGA, a new dynamic competitive coevolutionary genetic algorithm. We compare the performance of dLCGA to other known classes of CGAs for the Inventory Control Parameter optimization problem (ICP) and in particular show how it improves the results of the static version of LCGA. IN...

In this paper a new concept of ranking among the solutions of the same front, along with elite preservation mechanism and ensuring diversity through the nearest neighbor method is proposed for multi-objective genetic algorithms. This algorithm is applied on a set of benchmark multi-objective test problems and the results are compared with that of NSGA-II (a similar algorithm). The proposed algo...

Dynamical behavior of some electronic circuits involves signals with widely separated rates of variation. Numerical solution of ordinary differential systems describing such circuits may be achieved in an efficient way using multi-rate methods, which use different step sizes for each subsystem. In this paper we will test the performance of two multi-rate Runge-Kutta algorithms in terms of numer...

Heuristic optimizers are an important tool in academia and industry, and their performance-optimizing configuration requires a significant amount of expertise. As the proper configuration of algorithms is a crucial aspect in the engineering of heuristic algorithms, a significant research effort has been dedicated over the last years towards moving this step to the computer and, thus, make it au...

Decision support systems use On-Line Analytical Processing (OLAP) to analyze data by posing complex queries that require diierent views of data. Traditionally , a relational approach (ROLAP) has been taken to build such systems. More recently, multi-dimensional database techniques (MOLAP) have been applied to decision-support applications. Data is stored in multi-dimensional arrays which is a n...

We contribute to the theoretical understanding of variable length evolutionary algorithms. Such algorithms are very flexible but can encounter the bloat problem which means solutions grow during the optimization run without providing additional benefit. We explore two common mechanisms for dealing with this problem from a theoretical point of view and point out the differences of a parsimony an...

according to the current state of water resources and the increasing demand for water, the supply of future needs will be faced with serious constraints. on the one hand, the failure to supply sometimes causes social and political problems. on the other hand, improper exploitation of water resources will lead to irreparable damages. therefore, the use of optimization models for the planning of ...