Solving a new cost-oriented assembly line balancing problem by classical and hybrid meta-heuristic algorithms

Neural Computing and Applications - In this study, a new cost-oriented assembly line balancing problem is proposed and formulated. A single objective function consisting of minimizing the cost...     

A hybrid solution approach for fuzzy multiobjective dual supplier and material selection problem of carton box production systems

A novel optimization problem of carton box manufacturing industries is introduced in this paper. A mixed integer linear formulation with multiple objective functions is developed in order to determine the value of some criteria of carton raw sheets such as size, amount, and supplier under simultaneous minimization of multiple goals such as purchasing cost of raw sheets under discount policy, wastage remained from raw sheets, and quantity of surplus of carton boxes. In order to cope with the unstable market of this sector, some parameters of the proposed formulation such as demand value of the products and price given for raw sheets are assumed to be fuzzy numbers. To tackle such fuzzy multiobjective problem, first, the fuzzy problem is converted to a crisp form using the concepts of necessity‐based chance‐constrained modelling approach. Then a new hybrid form of the fuzzy programming approach is proposed to solve the obtained crisp multiobjective problem effectively. Computational experiments on a real case given by a carton box factory show the superior result of the proposed solution approach compared with the well‐known multiobjective solution methods taken from the literature.     

Prediction of water saturation in a tight gas sandstone reservoir by using four intelligent methods: a comparative study

Neural Computing and Applications - Reservoir water saturation is an important property of tight gas reservoirs. Improper calculation of water saturation leads to remarkable errors in following...     

Experimental study of seeding in genetic algorithms with non-binary genetic representation

Seeding is a technique used to leverage population diversity in genetic algorithms. This paper presents a quick survey of different seeding approaches, and evaluates one of the promising ones called the Seeding Genetic Algorithm. The Seeding GA does not include mutation, and it has been shown to work well on some GA-hard problems with binary representation, such as the Hierarchical If-and-Only-If or Deceptive Trap. This paper investigates the effectiveness of the Seeding GA on two problems with more complex non-binary representations: capacitated lot-sizing and single-machine scheduling. The results show, with statistical significance, that the new GA is consistently outperformed by the conventional GA, and that not including mutation is the main reason why. A detailed analysis of the results is presented and suggestions are made to enhance and improve the method.     

Resource provisioning for cloud applications: a 3-D,provident and flexible approach

The scalability feature of cloud computing attracts application service providers (ASPs) to use cloud application hosting. In cloud environments, resources can be dynamically provisioned on demand for ASPs. Autonomic resource provisioning for the purpose of preventing resources over-provisioning or under-provisioning is a widely investigated topic in cloud environments. There has been proposed a lot of resource-aware and/or service-level agreement (SLA)-aware solutions to handle this problem. However, intelligence solutions such as exploring the hidden knowledge on the Web users’ behavior are more effective in cost efficiency. Most importantly, with considering cloud service diversity, solutions should be flexible and customizable to fulfill ASPs’ requirements. Therefore, lack of a flexible resource provisioning mechanism is strongly felt. In this paper, we proposed an autonomic resource provisioning mechanism with resource-aware, SLA-aware, and user behavior-aware features, which is called three-dimensional mechanism. The proposed mechanism used radial basis function neural network in order to provide providence and flexibility features. The experimental results showed that the proposed mechanism reduces the cost while guarantees the quality of service.     

Novel resource allocation algorithms to performance and energy efficiency in cloud computing

The rapid growth in demand for computational power has led to a shift to the cloud computing model established by large-scale virtualized data centers. Such data centers consume enormous amounts of electrical energy. Cloud providers must ensure that their service delivery is flexible to meet various consumer requirements. However, to support green computing, cloud providers also need to minimize the cloud infrastructure energy consumption while conducting the service delivery. In this paper, for cloud environments, a novel QoS-aware VMs consolidation approach is proposed that adopts a method based on resource utilization history of virtual machines. Proposed algorithms have been implemented and evaluated using CloudSim simulator. Simulation results show improvement in QoS metrics and energy consumption as well as demonstrate that there is a trade-off between energy consumption and quality of service in the cloud environment.     

Effect of heat storage and fuel price on energy management and economics of micro CCHP cogeneration systems

In the present work, a typical combined cooling, heating and power (CCHP) system comprised of boiler, flat solar collectors, absorption chiller and heat storage tank was investigated. The described system was considered to supply the given electricity, cooling and heating demand of a residential building; with heating and cooling needs of 100 and 50 kW, respectively. To find the optimum hybrid configurations with high reliability, low costs, low fuel consumption and emissions, a computer program was provided by authors in FORTRAN language. Different fuel prices were considered in the present work. The results indicated that the optimal operation strategy changes with Boiler and NGG fuel prices while it also changes with increasing the number of solar collectors, heat storage capacity and consequently decreasing total annual emission.     

Rapid tooling analysis of Stereolithography injection mould tooling

Increasing competition in global markets is exerting intense pressure on companies to trim their product cycles continuously. As delivery times and costs of tools are on a downward trend, the modern tool manufacturer is under pressure to produce tools quickly, accurately and at a lower cost. Reducing the time to produce prototypes is a key to speed up the development of new products. Rapid tooling (RT) with particular regard to injection mould fabrication using rapid prototyping (RP) technology of Stereolithography (SL) may lead to savings in cost and time. In this paper, SL is used to directly build rapid injection mould tools for short run production. SL tools have been evaluated to analyse the maximum number of successful injections and quality of performance. SL epoxy tools were able to resist the injection pressure and temperature and 500 injections were achieved. The tool failure mechanisms during injection are investigated and tool failure either occurs due to excessive flexural stresses, or because of excessive shear stresses.     

On the Performance of Ag/Oil Nanofluids in Heat Transfer Enhancement in a Sinusoidal Tube: Constant Heat Flux Boundary Condition

The present work provides an empirical investigation on the thermal characteristics of Ag/oil nanofluids flow inside a sinusoidal tube under a constant heat flux boundary condition. Ag/oil nanofluids have been prepared in low‐volume concentrations of 0.011%, 0.044%, and 0.171%. The average size of the nanoparticles was 20 nm. A heated coil was attached to the upper and lower surface of the tube that satisfied the constant thermal boundary condition of 204 W. The experiment has been pursued at low Reynolds numbers less than 160. A loop was designed to keep the flow hydrodynamically fully developed during the experiment. The test case was a sinusoidal tube. Upper and lower surfaces of the tube have been designed sinusoidally. Moreover, the width of the plates was long enough, so the problem was not considerably affected by the three‐dimensional releasing effect. Convective heat transfer coefficient and Nusselt number were calculated. It has been observed that based on the acquired data of the present work, convective heat transfer coefficient increased up to 23% for the best case (nanofluid with a volume concentration of 0.171%) compared to the base fluid. This happened while the rise of the friction factor was very low. In addition, a comparison between the new results and the previous work by authors showed the positive performance of sinusoidal tubes in increasing the convective heat transfer coefficient (the average increase was calculated to be about 82%) compared to the annular tube.