Abstract—Spatio-temporal interpolation to generate voxel-field data in a space-time domain from observational data is indispensable to many spatiotemporal reconstruction and visualization of dynamic spatial phenomena. However, only very primitive interpolation methods such as nearest neighbor interpolation based on a Voronoi diagram are proposed for nominal or “class variable” data such as land...

In this paper we present PARADISEO1, an open source framework for flexible parallel and distributed design of hybrid metaheuristics. Flexibility means that the parameters such as data representation and variation operators can be evolved. It is inherited from the EO object-oriented library for evolutionary computation. PARADISEO provides different parallel and/or distributed models and allows a...

in this paper, we study the multi-depot vehiclerouting problem with inter-depot routes, in which the vehicles can replenish atintermediate depots. vehicles leave the origin depot with load on-board andserve customers until out of load. they may visit an intermediate depot toreplenish and finally return to the origin depot, completing their route. weinitiate a mathematical mixed integer programm...

according to recent developments of predicting methodsin financial markets, and since the stock price is one of the mostimportant factors for investment decision-making, and its predictioncan play an important role in this field, the aim of this study is toprovide a model to predict the stock price movement with highaccuracy. accordingly, a hybrid model for predicting the stock pricemovement us...

performance optimization of a single-effect lithium bromide water absorption refrigerationsystem is the subject of this paper. first, the thermodynamic model of the system wasderived based on thefirst and second law analysis of an absorption refrigeration cycle with libr-water as the working fluid pair.then, the effects of different design parameters such as the generator inlet hot water temper...

| We introduce a new optimization method based on a Genetic Algorithm (GA) mixed with Constraint Satisfaction Problem (CSP) techniques. The approach is designed for combinatorial problems whose search spaces are too large and/or objective functions too complex for usual CSP techniques and whose constraints are too complex for conventional genetic algorithm. The main idea is the handling of sub-...

This paper has developed a novel multiobjective function for optimal sizing and sitting ofDistributed Generation (DG) units and capacitor banks in simultaneous mode to improve reliabilityand reduce energy losses. The proposed function consists of four objectives: Cost of Energy NotSupplied (CENS), System Average Interruption Duration Index (SAIDI), costs of energy loss andinvestment. A novel st...

The main objective of this paper is to introduce a new intelligent optimization technique that uses a predictioncorrectionstrategy supported by a recurrent neural network for finding a near optimal solution of a givenobjective function. Recently there have been attempts for using artificial neural networks (ANNs) in optimizationproblems and some types of ANNs such as Hopfield network and Boltzm...

The fixed charge transportation problem (FCTP) is a deployment of the classical transportation problem in which a fixed cost is incurred, independent of the amount transported, along with a variable cost that is proportional to the amount shipped. Since the problem is considered as an NP-hard, the computational time grows exponentially as the size of the problem increases. In this pape...

the main objective of this paper is to introduce a new intelligent optimization technique that uses a predictioncorrectionstrategy supported by a recurrent neural network for finding a near optimal solution of a givenobjective function. recently there have been attempts for using artificial neural networks (anns) in optimizationproblems and some types of anns such as hopfield network and boltzm...