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Combinational circuits have become more vulnerable to soft errors (SEs) in each CMOS technology generation. Most of the prior studies use hardware redundancy in an attempt to harden the circuits against errors. However, redundancy increases the area and power consumption. Furthermore, the design constraints may not allow adding redundant resources to the final circuit. In this paper, we present a...
Considering the effects of machine breakdown and preventative maintenance (PM)on production scheduling in flowshop manufacturing cells, this paper focuses on investigating the joint optimization problem of flowshop sequence-dependent manufacturing cell scheduling and PM. A joint model is proposed and it aims to find the optimal production sequence of job families and individual jobs within each family...
The introduction of smart metering has brought more detailed information on the actual load profile of a house. With the ability to measure, comes the desire to control the load profile. Furthermore, advances in renewable energy have made the consumer to become supplier, known as Prosumer, who therefore also becomes interested in the detail of his load, and also his energy production. With the lowering...
In the past decades, divisible load scheduling has become an increasingly concerned field in the research of computer science. At the same time, the total system cost of data center has received worldwide attention, and the concept of green computing has been put forward. This paper investigates an cost-efficient divisible load scheduling using genetic algorithm. It focuses on finding an efficient...
A hybrid optimization algorithm is proposed for Job-Shop scheduling problem, which is based on the combination of adaptive genetic algorithm and improved ant algorithm. The algorithm gets the initial pheromone distribution using adaptive genetic algorithm at first, then runs improved ant algorithm. The algorithm utilizes the advantages of the two algorithms and overcomes their disadvantages. Experimental...
Cloud computing is the upcoming technology in current day scenario. It has emerged as a solution for providing resources to the consumers in the form of software, infrastructure or platform as a service. Cloud Service Storage enables users to synchronize their files across devices and also allows them to backup online. The main aim of this paper is to provide service optimization. Scheduling of services...
After analyzing different styles of designing specialty, the paper establishes a scheduling model based on genetic algorithms (GAs). This method is designed for optimizing parallel and batched maintenance tasks of multi-specialty and minimizing the time of recovering the battle effectiveness of combat units. The proposed method involves two steps. Firstly, the optimized sorting model of combat units...
Militaries involved in transportation of people and cargo need to be able to assess which tasks they can or cannot do given a specified fleet of heterogeneous platforms (such as vehicles or aircraft). We introduce the Stochastic Fleet Estimation under Steady State Tasking (SaFESST) model to determine which tasks will not be achievable. SaFESST is a bin-packing model which uses a fleet configuration...
This work presents a Genetic Algorithm (GA) based optimization technique, called GA-ParFnt, to find the Pareto frontier for optimizing data transfer versus job execution time in grids. As the performance of a generic GA is not suitable to find such Pareto relationship, several modifications are applied to it so that it can efficiently discover such relationship. The frontier curve representing this...
Logistics traffic scheduling is a key job for logistics activity, but there are some weak points, e.g. local optimum, premature convergence and slow convergence while we employ the traditional genetic algorithm to analyze that problem. Therefore, we need to improve the genetic algorithm to solve the vehicle routing problem. This paper builds up a mathematical model for the traffic scheduling problems...
Driver scheduling is an important part of the base of blocking. A better method of driver scheduling is advanced in this paper. First, a model is built, the optimization objective of which includes the opportunity cost of shifts and the least wage cost. Then a genetic algorithm is designed to get the optimization solution, and the driver scheduling model and algorithm is tested by the data of Route...
The increasing development of civil aviation transportation has caused serious congestion, which often results in low efficiency and potential risks of airport surface traffic system. In this paper, a new genetic encoding method different from previous ones is presented to solve the aircraft safe taxiing problems based on an optimization model with three types of conflict restrictions. The simulations...
The increasing development of civil aviation transportation has caused serious congestion, which often results in the low efficiency and the potential risks of airport surface traffic system. In this paper, a new genetic encoding method different from previous ones is presented to solve the aircraft safe taxiing problems based on an optimization model with three types of conflict restrictions. The...
Computational grids have become attractive and promising platforms for solving large-scale high-performance applications of multi-institutional interest. However, the management of resources and computational tasks is a critical and complex undertaking as these resources and tasks are geographically distributed and a heterogeneous in nature. This paper proposes a novel Rank Based Genetic Scheduler...
This paper presents a multi-objective post enrolment course timetabling problem as a new case study. We added a new soft constraint to the original single objective problem to both increase the complexity and represent a real world course timetabling problem. The new soft constraint introduced here attempts to minimize the total number of waiting timeslots in between courses for every student in a...
In this paper, satellite imaging scheduling of cooperative multiple centers, an example of multi-agent systems, is discussed with a proposal of a novel Cooperative CoEvolutionary Planning Algorithm (CCEPA). Considering the numbers of the multi-center and the characteristics of targets to be observed, CCEPA decomposes the tasks into smaller components and evolves multiple solutions in the form of cooperative...
This paper presents an experimental analysis of three algorithms for the Oil Derivatives Distribution Problem with two objectives. The problem consists in scheduling the transmission of oil products from source nodes to terminals in due times. The minimization of two objectives is considered: delivery time and fragmentation, that is, the consecutive transmission of distinct products in the same polyduct...
Decisions for admission scheduling in hospitals are a class of optimization problems constrained by many factors. Instead of scheduling the admission of patients directly, this paper proposes a genetic algorithm (GA) designed for the optimization of a long-term admission strategy for the ophthalmology department in hospitals. For the optimization of admission strategy, we devise a coding scheme of...
In network optimization problems, the application of conventional integrated selection and scheduling solution methods becomes complicated when the size of the problems, such as real life project management and transportation problems, get bigger. Additionally, the problems often consist of disjunctive networks, which traditionally results in separating the steps of the integrated approach. When the...
Capability Maturity Model Integration (CMMI) helps organizations to improve software development processes. But it contains very little information on process dynamics. It doesn't address the following issues like Specific tools, methods and technologies to be followed, Issues in Human resource management, People management methodology and cost attached to people manager. In this paper we focus on...
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