A bi-objective genetic algorithm approach to risk mitigation in project scheduling

A problem of risk mitigation in project scheduling is formulated as a bi-objective optimization problem, where the expected makespan and the expected total cost are both to be minimized. The expected total cost is the sum of four cost components: overhead cost, activity execution cost, cost of reducing risks and penalty cost for tardiness. Risks for activities are predefined. For each risk at an activity, various levels are defined, which correspond to the results of different preventive measures. Only those risks with a probable impact on the duration of the related activity are considered here. Impacts of risks are not only accounted for through the expected makespan but are also translated into cost and thus have an impact on the expected total cost. An MIP model and a heuristic solution approach based on genetic algorithms (GAs) is proposed. The experiments conducted indicate that GAs provide a fast and effective solution approach to the problem. For smaller problems, the results obtained by the GA are very good. For larger problems, there is room for improvement

A biobjective genetic algorithm approach to project scheduling under risk

A problem of risk mitigation in project scheduling is formulated as a bi-objective optimization problem, where the expected makespan and the expected total cost are both to be minimized. The expected total cost is the sum of four cost components: overhead cost, activity execution cost, cost of reducing risks and penalty cost for tardiness. Risks for activities are predefined. For each risk at an activity, various levels are defined, which correspond to the results of different preventive measures. Only those risks with a probable impact on the duration of the related activity are considered here. Impacts of risks are not only accounted for through the expected makespan but are also translated into cost and thus have an impact on the expected total cost. An MIP model and a heuristic solution approach based on genetic algorithms (GAs) is proposed and tested. The experiments conducted indicate that GAs provide a fast and effective solution approach to the proble m. For smaller problems, the results obtained by the GA are very good. For larger problems, there is room for improvement

Stability of Peripheral Milling Operations with Long End Mills

AbstractThis paper presents dynamic modelling of peripheral milling systems with axially varying dynamics. The end mill is divided into differential elements along the cutter axis, and discrete nodes are assigned along the axial depth of cut. The cutting forces, which include regenerative and process damping components, are distributed to nodes. The equation of motion is transformed into modal space as periodic, delayed differential equations which cover one tooth period for regular, and one spindle period for variable pitch cutters. The directional coefficients are averaged and the stability is solved in frequency domain using Nyquist criterion. The presented model is experimentally verified in peripheral milling tests with low radial and high axial depth of cut

Fast Adaptive Robust Differentiator Based Robust-Adaptive Control of Grid-Tied Inverters with a New L Filter Design Method

In this research, a new nonlinear and adaptive state feedback controller with a fast-adaptive robust differentiator is presented for grid-tied inverters. All parameters and external disturbances are taken as uncertain in the design of the proposed controller without the disadvantages of singularity and over-parameterization. A robust differentiator based on the second order sliding mode is also developed with a fast-adaptive structure to be able to consider the time derivative of the virtual control input. Unlike the conventional backstepping, the proposed differentiator overcomes the problem of explosion of complexity. In the closed-loop control system, the three phase source currents and direct current (DC) bus voltage are assumed to be available for feedback. Using the Lyapunov stability theory, it is proven that the overall control system has the global asymptotic stability. In addition, a new simple L filter design method based on the total harmonic distortion approach is also proposed. Simulations and experimental results show that the proposed controller assurances drive the tracking errors to zero with better performance, and it is robust against all uncertainties. Moreover, the proposed L filter design method matches the total harmonic distortion (THD) aim in the design with the experimental result

Multiobjective genetic algorithm approaches to project scheduling under risk

In this thesis, project scheduling under risk is chosen as the topic of research. Project scheduling under risk is defined as a biobjective decision problem and is formulated as a 0-1 integer mathematical programming model. In this biobjective formulation, one of the objectives is taken as the expected makespan minimization and the other is taken as the expected cost minimization. As the solution approach to this biobjective formulation genetic algorithm (GA) is chosen. After carefully investigating the multiobjective GA literature, two strategies based on the vector evaluated GA are developed and a new GA is proposed. For these three GAs first the parameters are investigated through statistical experimentation and then the values are decided upon. The chosen parameters are used for the computational study part of this thesis. In this thesis three improvement heuristics are developed also to further improve the GA solutions. The aim of these improvement heuristics is to decrease the expected cost of the project while keeping the expected duration of the project fixed. These improvement heuristics are implemented at the end of the proposed GA and used to improve the results of the proposed GA. Finally the GAs and improvement heuristics are tested on three different sets of problems. The results are evaluated by pairwise comparisons of algorithms and of heuristics. Also an approximation of the true Pareto front is generated using the commercial mathematical modelling program, GAMS. The results are compared to that approximation and they seem comparable to that solution. The results of the improvement heuristics are also compared against each other and the performance of the heuristics is reported in detail

Experimental determination of optimal clamping torque for AB-PEM fuel cell

Polymer electrolyte Membrane (PEM) fuel cell is an electrochemical device producing electricity by the reaction of hydrogen and oxygen without combustion. PEM fuel cell stack is provided with an appropriate clamping torque to prevent leakage of reactant gases and to minimize the contact resistance between gas diffusion media (GDL) and bipolar plates. GDL porous structure and gas permeability is directly affected by the compaction pressure which, consequently, drastically change the fuel cell performance. Various efforts were made to determine the optimal compaction pressure and pressure distributions through simulations and experimentation. Lower compaction pressure results in increase of contact resistance and also chances of leakage. On the other hand, higher compaction pressure decreases the contact resistance but also narrows down the diffusion path for mass transfer from gas channels to the catalyst layers, consequently, lowering cell performance. The optimal cell performance is related to the gasket thickness and compression pressure on GDL. Every stack has a unique assembly pressure due to differences in fuel cell components material and stack design. Therefore, there is still need to determine the optimal torque value for getting the optimal cell performance. This study has been carried out in continuation of development of Air breathing PEM fuel cell for small Unmanned Aerial Vehicle (UAV) application. Compaction pressure at minimum contact resistance was determined and clamping torque value was calculated accordingly. Single cell performance tests were performed at five different clamping torque values i.e 0.5, 1.0, 1.5, 2.0 and 2.5 N m, for achieving optimal cell performance. Clamping pressure distribution tests were also performed at these torque values to verify uniform pressure distribution at optimal torque value. Experimental and theoretical results were compared for making inferences about optimal cell performance. A clamping torque value of 1.5 N m was determined experimentally to be the best for getting optimal performance as well as uniform pressure distribution for this specific fuel cell

Endocan Overexpression in Pterygium

WOS: 000403262500013PubMed ID: 28410547Purpose: The aim of this study was to evaluate the possible role of endocan in the pathogenesis of pterygium. Methods: The study was conducted on 33 patients with primary pterygium and 20 control subjects with normal bulbar conjunctiva. Patients with pterygium were graded into 3 groups as atrophic, fleshy, and intermediate, according to the Tan classification. Primary nasal pterygia and normal bulbar conjunctivas were surgically removed. Endocan expression was immunohistochemically investigated. Results: Endocan expression in epithelial and endothelial cells was statistically significantly higher in pterygium tissues than control tissues (P = 0.001). No significant correlation was observed between pterygium classification groups and endocan expression in both epithelial and endothelial cells (P > 0.05). Conclusions: The results suggest that endocan may have a role in the pathogenesis of pterygium

Development of three-roving ring yarn production system

This study focuses on development of three-roving yarn production system that is inspired from siro-spun technology. Roving funnel and delivery cylinder used in siro-spun technology are redesigned for three-roving yarn production and attached on conventional system. Three-roving yarns produced in ring spinning machine are compared with three plied yarns in terms of physical, mechanical and structural properties. For better assessment of this new system, different raw material types are used in yarn production. Results show that three-roving yarns have better hairiness values and similar mechanical properties for all raw material types. However, unevenness still needs to be improved by further developments on this new system

Development of three-roving ring yarn production system

450-456This study focuses on development of three-roving yarn production system that is inspired from siro-spun technology. Roving funnel and delivery cylinder used in siro-spun technology are redesigned for three-roving yarn production and attached on conventional system. Three-roving yarns produced in ring spinning machine are compared with three plied yarns in terms of physical, mechanical and structural properties. For better assessment of this new system, different raw material types are used in yarn production. Results show that three-roving yarns have better hairiness values and similar mechanical properties for all raw material types. However, unevenness still needs to be improved by further developments on this new system