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Motivated by the growing demand of accuracy and low computational time in optimizing functions in various fields of engineering, an approach has been presented using the technique of parallel computing. The parallelization has been carried out on one of the simplest and flexible optimization algorithms, namely the particle swarm optimization (PSO) algorithm. PSO is a stochastic population global optimizer...
Optimization problems are ubiquitous and consequential. In fact every sphere of human activity that can be quantified can be formulated as an optimization problem. The focus of this work is on Global Optimization which is not only desirable but also necessary in many cases. In the past few decades several Global optimization algorithms have been suggested in literature out of which stochastic, population...
The weapon target assignment problem can be modeled as an optimization problem in which the objective is to assign weapons to target in order to maximize the optimum target damage value. The mathematical model of the problem is subject to various constraints depending on the availability of weapons The objective function of the problem is non linear and the constraints are linear in nature. Also,...
The coexistence of multimedia services in e-communication systems, with varying bandwidth utilization characteristics, impedes the efficiency of rate control and thereby impacts on the Quality of Service (QoS), in terms of low throughput. As such, the rate control for multimedia flows remains an open problem. This paper proposes a memetic optimization approach to rate allocation of multiclass services...
Most optimization problems have constraints of different types (e.g., physical, time, geometric, etc.), which modify the shape of the search space. We propose an ecologically inspired invasive weed optimization (IWO) algorithm to solve the constrained real-parameter optimization problems. Central to our approach is a parameter-free penalty function that we introduce. The adaptive nature of the penalty...
A model of the bee hive that clearly separates the self-organizing decision-making behaviour of the bees in the hive and the problem-specific behaviour of the bees outside the hive is presented. This separation allows for the applications of the model for different problem domains. Results of the application to three problem domains are presented - web search, function optimization and hierarchical...
Evolutionary algorithms have been widely used to solve difficult constrained optimization problems. However, evolutionary algorithms are intrinsically unconstrained optimization techniques. Constraint handling is mostly incorporated additionally and its choice has great bearing on the quality of the solution. Stochastic ranking was introduced as an improvement over feasibility rules for handling constraints...
In this paper we have used a real coded genetic algorithm for finding the global minimum energy conformation of two small molecules viz. Pseudoethane and 1,2,3-trichloro-l-fluoro-propane based on a potential function. Finding the global minimum of this function is very difficult because it has a large number of local minima, which grows exponentially with molecule size. Computational results are obtained...
Invasive weed optimization (IWO) has been found to be a simple but powerful algorithm for function optimization over continuous spaces. It has reportedly outperformed many types of evolutionary algorithms and other search heuristics when tested over both benchmark and real-world problems. However the performance of most search heuristics deteriorates severely when applied to the task of optimization...
This paper presents the design of a decentralized storage scheme to support multi-dimensional range queries over sensor networks. We build a distributed k-d tree based index structure over sensor network, so as to efficiently map high dimensional event data to a two-dimensional space of sensors while preserving the proximity of events. We propose a dynamic programming based methodology to control...
This paper presents an empirical analysis of the performance of differential evolution (DE) variants on different classes of unconstrained global optimization benchmark problems. This analysis has been undertaken to identify competitive DE variants which perform reasonably well on a range of problems with different features. Towards this, fourteen DE variants were implemented and tested on 14 high...
This paper presents a new diversity guided particle swarm optimization algorithm (PSO) named beta mutation PSO or BMPSO for solving global optimization problems. The BMPSO algorithm makes use of an evolutionary programming based mutation operator to maintain the level of diversity in the swarm population, thereby maintaining a good balance between the exploration and exploitation phenomena and preventing...
Consider a first order, linear and time-invariant discrete time system driven by Gaussian, zero mean white process noise, a pre-processor that accepts noisy measurements of the state of the system, and an estimator. The pre-processor and the estimator are not co-located, and, at every time-step, the pre-processor sends either a real number or an erasure symbol to the estimator. We seek the pre-processor...
In this paper, we consider modulation codes for practical multilevel flash memory storage systems with q cell levels. Instead of maximizing the lifetime of the device we maximize the average amount of information stored per cell-level, which is defined as storage efficiency. Using this framework, we show that the worst-case criterion and the average-case criterion are two extreme cases of our objective...
Mechanisms for allocation of one or many goods to a number of agents are proposed in this paper. The goal is to propose mechanisms in a general setting where the goods might be divisible or indivisible. A mechanism in the Groves class that is dominant strategy incentive compatible and almost budget balanced is obtained. In the case of one or more indivisible goods, the proposed mechanisms fall back...
Sustainable development is widely practiced by many engineers, academicians and policy makers for making the industries environmental friendly, to obtain sustainability in any industry there are many methods. Resources utilized in an industry should be identified properly in various processes and its utilization is to be optimized to increase the environmental performance of the industry. Ecomapping...
Manually tuning tens to hundreds of configuration parameters in a complex software system like a database or an application server is an arduous task. Recent work has looked into automated approaches for recommending good configuration settings that adaptively search the full space of possible configurations. These approaches are based on conducting experiments where each experiment runs the system...
Temporal and spatial localities are basic concepts in operating systems, and storage systems rely on localities to perform well. Surprisingly, it is difficult to quantify the localities present in workloads and how localities are transformed by storage data path components in metrics that can be compared under diverse settings. In this paper, we introduce stack- and block-affinity metrics to quantify...
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