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I. Ismail - One of the best experts on this subject based on the ideXlab platform.
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combinatorial optimization comparison of heuristic algorithms in travelling salesman problem
Archives of Computational Methods in Engineering, 2019Co-Authors: Hanif A. Halim, I. IsmailAbstract:The Travelling Salesman Problem (TSP) is an NP-hard problem with high number of possible solutions. The complexity increases with the factorial of n nodes in each specific problem. Meta-heuristic algorithms are an optimization algorithm that able to solve TSP problem towards a satisfactory solution. To date, there are many meta-heuristic algorithms introduced in literatures which consist of different philosophies of intensification and diversification. This paper focuses on 6 heuristic algorithms: Nearest Neighbor, Genetic Algorithm, Simulated Annealing, Tabu Search, Ant Colony Optimization and Tree Physiology Optimization. The study in this paper includes comparison of computation, accuracy and convergence.
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Tree Physiology optimization on SISO and MIMO PID control tuning
Neural Computing and Applications, 2018Co-Authors: A. Hanif Halim, I. IsmailAbstract:The tuning of proportional–integral–derivative (PID) controller is essential for any control application in order to ensure the best performance by step change or disturbance. This paper presents the tuning of PID controller for single-input single-output (SISO) and multiple-input multiple-output (MIMO) control systems using Tree Physiology optimization (TPO). TPO is a metaheuristic algorithm inspired from a plant growth system derived based on the idea of plant architecture and Thornley model (TM). The basic principle of TM simplifies the plant growth into shoots and roots part. The plant shoots grow towards sunlight with the help of nutrients supplied by the root system in order to undergo photosynthesis process, a process of converting light photon into carbon. The carbon gain from the shoots extension will be supplied to the root system in order for the root to grow and search for water plus nutrients. As a result, the nutrients are supplied upwards towards shoot system for further extension. This concept runs iteratively in order to ensure optimum plant growth. The iterative search of shoot towards better light supported by the root counterparts leads to an optimization idea of TPO algorithm. TPO also has a unique exploration strategy due to its multiple branches and shoots that can be defined by user. This concept may improve the search mechanism with a better trade-off between diversification and intensification search. A simulation of SISO control system and an industrial application of MIMO control are applied to demonstrate the effectiveness of the proposed algorithm and compared with other optimization methods such as particle swarm optimization, Ziegler–Nichols, Tyreus–Luyben and Chien–Hrones–Reswick methods. The results clearly exhibit the capability of TPO algorithm towards finding the optimum PID parameters for SISO and MIMO process with faster settling time and better performance with respect to other methods.
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Tree Physiology Optimization in Constrained Optimization Problem
TELKOMNIKA (Telecommunication Computing Electronics and Control), 2018Co-Authors: A. Hanif Halim, I. IsmailAbstract:Metaheuristic algorithms are proven to be more effective on finding global optimum in numerous problems including the constrained optimization area. The algorithms have the capacity to prevail over many deficiencies in conventional algorithms. Besides of good quality of performance, some metaheuristic algorithms have limitations that may deteriorate by certain degree of difficulties especially in real-world application. Most of the real-world problems consist of constrained problem that is significantly important in modern engineering design and must be considered in order to perform any optimization task. Therefore, it is essential to compare the performance of the algorithm in diverse level of difficulties in constrained region. This paper introduces Tree Physiology Optimization (TPO) algorithm for solving constrained optimization problem and compares the performance with other existing metaheuristic algorithms. The constrained problems that are included in the comparison are three engineering design and nonlinear mathematic problems. The difficulties of each proposed problem are the function complexity, number of constraints, and dimension of variables. The performance measure of each algorithm is the statistical results of finding the global optimum and the convergence towards global optimum.
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Tree Physiology Optimization in Benchmark Function and Traveling Salesman Problem
Journal of Intelligent Systems, 2017Co-Authors: A. Hanif Halim, I. IsmailAbstract:Abstract Nature has the ability of sustainability and improvisation for better survival. This unique characteristic reflects a pattern of optimization that inspires the computational intelligence toward different scopes of optimization: a nondeterministic optimization approach or a nature-inspired metaheuristic algorithm. To date, there are many metaheuristic algorithms introduced with good promising results and also becoming a powerful method for solving numerous optimization problems. In this paper, a new metaheuristic algorithm inspired from a plant growth system is proposed, which is defined as Tree Physiology optimization (TPO). A plant growth consists of two main counterparts: plant shoots and roots. Shoots extend to find better sunlight for the photosynthesis process that converts light and water supplied from the roots into energy for plant growth; at the same time, roots elongate in the opposite way in search for water and nutrients for shoot survival. The collaboration from both systems ensures plant sustainability. This idea is transformed into an optimization algorithm: shoots with defined branches find the potential solution with the help of roots variable. The shoots-branches extension enhances the search diversity and the root system amplifying the search via evaluated fitness. To demonstrate its effectiveness, two different classes of problem are evaluated: (1) a continuous benchmark test function compared to particle swarm optimization (PSO) and genetic algorithm (GA) and (2) an NP-hard problem with the traveling salesman problem (TSP) compared to GA and nearest-neighbor (NN) algorithm. The simulation results show that TPO outperforms PSO and GA in all problem characteristics (flat surface and steep-drop with a combination of many local minima and plateau). In the TSP, TPO has a comparable result to GA.
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Tree Physiology Optimization tuning rule for Proportional-Integral control
MATEC Web of Conferences, 2017Co-Authors: A. Hanif Halim, I. IsmailAbstract:This paper presents a tuning correlation for Proportional-Integral (PI) controller parameters using Tree Physiology Optimization algorithm (TPO). TPO is a metaheuristic algorithm that has parallel search strategy inspired from plant growth system. The parallel search is referred to the plant branches and leaves that able to diversify the search space and therefore finding promising results in much faster iterations. The exploration is amplified from roots growth counterparts. In the proposed method, a tuning correlation of PI-controller using TPO is established and the performances of correlated parameters are compared with Ciancone correlation. The idea of correlation tuning is to reduce the optimization time consumption and engineering efforts in controller tuning. The results shown that the tuning correlation of TPO is able to find good PI parameters with lesser error.
Hanif A. Halim - One of the best experts on this subject based on the ideXlab platform.
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combinatorial optimization comparison of heuristic algorithms in travelling salesman problem
Archives of Computational Methods in Engineering, 2019Co-Authors: Hanif A. Halim, I. IsmailAbstract:The Travelling Salesman Problem (TSP) is an NP-hard problem with high number of possible solutions. The complexity increases with the factorial of n nodes in each specific problem. Meta-heuristic algorithms are an optimization algorithm that able to solve TSP problem towards a satisfactory solution. To date, there are many meta-heuristic algorithms introduced in literatures which consist of different philosophies of intensification and diversification. This paper focuses on 6 heuristic algorithms: Nearest Neighbor, Genetic Algorithm, Simulated Annealing, Tabu Search, Ant Colony Optimization and Tree Physiology Optimization. The study in this paper includes comparison of computation, accuracy and convergence.
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Online PID controller tuning using Tree Physiology optimization
2016 6th International Conference on Intelligent and Advanced Systems (ICIAS), 2016Co-Authors: Hanif A. Halim, I. IsmailAbstract:This paper presents the tuning of Proportional Integral Derivative (PID) controller parameter using a novel Tree Physiology Optimization (TPO). TPO is another variant of metaheuristic optimization that inspired from a plant growth system. In the proposed method, every possible solution denoted as Tree-shoots is driven by variables from the root system. The concept is inspired from the propagation of shoot system towards better sunlight. At the same time, the root system receive fitness value which then triggers root extension towards a better possible factor and then supplied to the shoot system. This iterative correlation leads towards optimum solution. A simulation of online PID-tuning is applied to demonstrate the effectiveness of proposed algorithm and compared with other optimization method which are Particle Swarm Optimization (PSO) and Ziegler-Nichols (Z-N) method.
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Nonlinear plant modeling using neuro-fuzzy system with Tree Physiology optimization
2013 IEEE Student Conference on Research and Developement, 2013Co-Authors: Hanif A. Halim, I. IsmailAbstract:This paper introduces a theoretical new approach for training the adaptive-network-based fuzzy inference system (ANFIS) using Tree Physiology Optimization (TPO). The TPO is a heuristic method based on Tree Physiology. The method will be applied to nonlinear dynamic system.
Kevin L Griffin - One of the best experts on this subject based on the ideXlab platform.
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proximal remote sensing of Tree Physiology at northern Treeline do late season changes in the photochemical reflectance index pri respond to climate or photoperiod
Remote Sensing of Environment, 2019Co-Authors: Jan U H Eitel, Kevin L Griffin, Andrew J Maguire, Natalie T Boelman, Lee A Vierling, Johanna Jensen, Troy S Magney, Peter J MahoneyAbstract:Abstract Relatively little is known of how the world's largest vegetation transition zone – the Forest Tundra Ecotone (FTE) – is responding to climate change. Newly available, satellite-derived time-series of the photochemical reflectance index (PRI) across North America and Europe could provide new insights into the physiological response of evergreen Trees to climate change by tracking changes in foliar pigment pools that have been linked to photosynthetic phenology. However, before implementing these data for such purpose at these evergreen dominated systems, it is important to increase our understanding of the fine scale mechanisms driving the connection between PRI and environmental conditions. The goal of this study is thus to gain a more mechanistic understanding of which environmental factors drive changes in PRI during late-season phenological transitions at the FTE – including factors that are susceptible to climate change (i.e., air- and soil-temperatures), and those that are not (photoperiod). We hypothesized that late-season phenological changes in foliar pigment pools captured by PRI are largely driven by photoperiod as opposed to less predictable drivers such as air temperature, complicating the utility of PRI time-series for understanding climate change effects on the FTE. Ground-based, time-series of PRI were acquired from individual Trees in combination with meteorological variables and photoperiod information at six FTE sites in Alaska. A linear mixed-effects modeling approach was used to determine the significance (α = 0.001) and effect size (i.e., standardized slope b*) of environmental factors on late-seasonal changes in the PRI signal. Our results indicate that photoperiod had the strongest, significant effect on late-season changes in PRI (b* = 0.08, p
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age related decline of stand biomass accumulation is primarily due to mortality and not to reduction in npp associated with individual Tree Physiology Tree growth or stand structure in a quercus dominated forest
Journal of Ecology, 2012Co-Authors: Matthew H Turnbull, David T Tissue, James D Lewis, Rob Carson, William S F Schuster, David Whitehead, Adrian S Walcroft, Kevin L GriffinAbstract:Age-related reductions in stand biomass accumulation are frequently observed in old-growth forests. The phenomenon may be caused by reduced production, increased mortality or both. The relative importance of production and mortality is not well studied, so the mechanisms controlling age-related decline of stand biomass accumulation remain unclear. In this study, conducted in a Quercus-dominated deciduous forest in the Northeastern USA, we examined whether age-related decline in stand above-ground biomass (AGB) accumulation could be explained by reduction of above-ground net primary production (NPP) (growth of surviving Trees) that may be associated with (i) physiological constraints within individual Trees or (ii) changes in stand structure, or by (iii) age-related, increasing Tree mortality in stands up to 135years old. Few previous studies have tested these hypotheses simultaneously within the same forest. We did not find evidence for a reduction in individual Tree growth associated with age-related physiological constraints, in terms of foliar carbon assimilation capacity, photosynthesis/respiration balance, nitrogen availability or hydraulic constraints on carbon gain. Over the period of 1937-2006, we did not observe alterations in stand structure, and the above-ground NPP of the Quercus forest was generally stable. However, we did find that the primary mechanism driving age-related decline of stand AGB accumulation was biomass loss due to the death of large, dominant Trees. Our results indicate that shifts in mortality from the loss of small Trees to the loss of large Trees, rather than changes in above-ground NPP, drives age-related decline in stand AGB accumulation in this forest. Synthesis.We found that within the range of stand development stages analysed, the age-related decline of stand AGB accumulation in a Quercus-dominated forest was primarily due to mortality of large, dominant Trees and not due to changes in above-ground NPP associated with Tree Physiology, individual Tree growth or stand structure. This result indicates that Tree demography and the influence of climate change on disturbances may need to be integrated into models to predict the change of above-ground carbon stock of some old-growth forests.
Tancrède Almeras - One of the best experts on this subject based on the ideXlab platform.
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Mechanical analysis of the strains generated by water tension in plant stems. Part II: strains in wood and bark and apparent compliance
Tree Physiology, 2008Co-Authors: Tancrède AlmerasAbstract:Tree stems shrink in diameter during the day and swell during the night in response to changes in water tension in the xylem. Stem shrinkage can easily be measured in a nondestructive way, to derive continuous information about Tree water status. The relationship between the strain and the change in water tension can be evaluated by empirical calibrations, or can be related to the structure of the plant.A mechanical analysis was performed to make this relationship explicit. The stem is modeled as a cylinder made of multiple layers of tissues, including heartwood, sapwood, and inner and outer bark. The effect of changes in water tension on the apparent strain at the surface of a tissue is quantified as a function of parameters defining stem anatomy and the mechanical properties of the tissues. Various possible applications in the context of Tree Physiology are suggested.
Peter J Mahoney - One of the best experts on this subject based on the ideXlab platform.
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proximal remote sensing of Tree Physiology at northern Treeline do late season changes in the photochemical reflectance index pri respond to climate or photoperiod
Remote Sensing of Environment, 2019Co-Authors: Jan U H Eitel, Kevin L Griffin, Andrew J Maguire, Natalie T Boelman, Lee A Vierling, Johanna Jensen, Troy S Magney, Peter J MahoneyAbstract:Abstract Relatively little is known of how the world's largest vegetation transition zone – the Forest Tundra Ecotone (FTE) – is responding to climate change. Newly available, satellite-derived time-series of the photochemical reflectance index (PRI) across North America and Europe could provide new insights into the physiological response of evergreen Trees to climate change by tracking changes in foliar pigment pools that have been linked to photosynthetic phenology. However, before implementing these data for such purpose at these evergreen dominated systems, it is important to increase our understanding of the fine scale mechanisms driving the connection between PRI and environmental conditions. The goal of this study is thus to gain a more mechanistic understanding of which environmental factors drive changes in PRI during late-season phenological transitions at the FTE – including factors that are susceptible to climate change (i.e., air- and soil-temperatures), and those that are not (photoperiod). We hypothesized that late-season phenological changes in foliar pigment pools captured by PRI are largely driven by photoperiod as opposed to less predictable drivers such as air temperature, complicating the utility of PRI time-series for understanding climate change effects on the FTE. Ground-based, time-series of PRI were acquired from individual Trees in combination with meteorological variables and photoperiod information at six FTE sites in Alaska. A linear mixed-effects modeling approach was used to determine the significance (α = 0.001) and effect size (i.e., standardized slope b*) of environmental factors on late-seasonal changes in the PRI signal. Our results indicate that photoperiod had the strongest, significant effect on late-season changes in PRI (b* = 0.08, p
