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Group role assignment (GRA) with flexible formation (called GRAFF) is a complex problem. The solution with GRA-Based on Exhaustive Search (GRA-ES) is too complex to be practical and the solution with Linear Programming-Based Algorithm (LPBA), implementing by Matlab and IBM ILOG CPLEX package, do not work well when the search space exceeds an extent. This paper proposes a solution to solve GRAFF based...
With the frequent occurrence of large-scale disasters, such as landslide and earthquake, timely and effective emergency resource scheduling becomes more and more important. Lots of disasters need multi-period rescue to satisfy the demand of disaster areas. In order to find a better plan to achieve the multi-period disaster relief, in this paper, a multi-period emergency resource scheduling problem...
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...
Cloud computing is the latest need of the hour network which is convenient. It is an on-demand network accessed over a shared group of computing resources. Only minimal management effort is needed to be released with no communication with a service-provider. Optimization problem such as Invasive Weed Optimization is used in cloud computing but the challenges in this technique is its premature convergence...
Many computing systems today are heterogeneous in that they consist of a mix of different types of processing units (e.g., CPUs, GPUs). Each of these processing units has different performance capabilities and energy consumption characteristics. Job mapping and scheduling play a crucial role in such systems as they strongly affect the overall system performance, energy consumption, peak power and...
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...
Integrated preventive maintenance (PM) and production scheduling problem has become one of research hotspots, but few research discusses the topic under uniform parallel machine system with deterioration effect. In this article, both characteristics of uniform parallel machines, deterioration effect of machine and job are considered, flexible PM strategy is adopted and integrated bi-objective optimization...
This paper mainly focuses on the method of timetable multi-objective optimization considering the randomness of passengers flow. The passenger flow model is established based on the normal distribution of the passenger flow, which is verified through the testing hypotheses for the number of passengers getting on and off the train. In assessment of energy consumption, the train operation between the...
Energy consumers oftentimes suffer some element of discomfort associated with the implementation of demand response programs as they aim to follow a suggested energy consumption profile generated from scheduling algorithms for the purpose of optimizing grid performance. This is because people naturally do not like to be told what to do or when to use their appliances. Although advances in renewable...
This paper presents a GISMOO algorithm adaptation to solve a multi-objective permutation flowshop with sequence-dependent setup times. The makespan and the total tardiness are the two objectives studied. Numerical experiments on various benchmarks from the literature were performed, to compare the performance of the adapted GISMOO algorithm with the NSGA-II algorithm. The results indicate that our...
The Gravitational Search Algorithm (GSA) is a nature inspired optimization algorithm which is based on Newton's law of gravity and law of motion. Biogeography Based Optimization (BBO) is also another nature inspired optimization algorithm based on the concept of biogeography (migration and mutation among population). Both of these optimization technique are population based and individually have been...
Federated Clouds are infrastructures arranging physical resources from different datacenters. A Cloud broker intermediates between users and datacenters to support the execution of jobs through Virtual Machines (VM). We exploit federated Clouds to run CPU-intensive jobs, in particular, Parameter Sweep Experiments (PSE). Specifically, we study a broker-level scheduler based on Ant Colony Optimization...
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...
Cloud computing environments mainly focus on the delivery of resources, platforms, and applications as services to users over the Internet. Cloud promises users access to as many resources as they need, making use of an elastic provisioning of resources. The cloud technology has gained popularity in recent years as the new paradigm in the IT industry. The number of users of Cloud services has been...
Grid computing proposes a dynamic and earthly distributed organization of resources that harvest ideal CPU cycle to drift advance computing demands and accommodate user's prerequisites. Heterogeneous gridsdemand efficient allocation and scheduling strategies to cope up with the expanding grid automations. In order to obtain optimal scheduling solutions, primary focus of research has shifted towards...
Scheduling is a vital issue in cloud computing in order to facilitate optimized usage of resources as in today's global and competitive environment the use of scarce resource in the best possible way is very important. Heuristic based algorithms are used in optimization techniques as they are class of heuristic approaches that have their inspirations from metaheuristics which are a general framework...
Scheduling is a vital issue in cloud computing in order to facilitate optimized usage of resources. Genetic algorithms are used in optimization techniques as they are class of heuristic approaches that have their inspirations from evolutionary ideas of natural evolution. The cloud scheduling optimization problem is modelled as a population of candidate solutions and the genetic algorithm is applied...
Cloud computing is a distributed computing model which enables developers to automatically deploy applications during task allocation and storage distribution. Cloud computing intends to share a pool of virtualized computer resources and equipment's of computation, storage and information. Scheduling is the most important complex part in cloud computing. The ultimate aim of global scheduler is to...
Train operation adjustment is a kind of real-time multi-objective large scale combination optimization problem with multi-restriction. A novel immune genetic algorithm based on artificial immune algorithm and genetic algorithm is put forward. Then scheduling optimization model for two-way marshalling train is proposed, which is solved by the proposed immune genetic algorithm. Finally, an instance...
As more and more fossil fuels are burned in order to keep up with the overgrowing demand for energy it is becoming increasingly necessary to look for alternative energy sources. Reducing peak-time energy demand is important to make the best use of renewable energies. In this paper we present an Ant Colony Optimization (ACO) based approach for the problem of scheduling tasks so as to minimize peak-times...
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