Influence of land classification systems on timber harvest scheduling models

1990 ◽  
Vol 20 (2) ◽  
pp. 172-178 ◽  
Author(s):  
M. S. Jamnick ◽  
L. S. Davis ◽  
J. K. Gilless
Keyword(s):  
Objective Function ◽  
Timber Harvest ◽  
Management Unit ◽  
Harvest Scheduling ◽  
Land Classification ◽  
Decision Variables ◽  
Optimal Harvest ◽  
Stand Type ◽  
Objective Function Values ◽  
Scheduling Models

Differences between linear program based timber harvest schedules that use decision variables based on stand types (homogeneous but generally noncontiguous areas) and management units (generally heterogeneous but contiguous areas) were investigated. It was proposed that (i) optimal harvest schedules identified using stand type decision variables should have larger present net value objective function values than those identified using models with management unit decision variables, (ii) optimal present net value objective function values in management unit models should decline as management unit size is increased, and (iii) as the number of management choices increases, differences between stand type and management unit optimal present net values should decrease. The propositions were tested using 48 linear programming timber harvest scheduling models constructed for the University of California's Blodgett Forest Experiment Station. These models, which form 12 model groups, differ in the numbers and type of prescriptions considered for existing or regenerated stands, and harvest flow or ending inventory policies. The results generally supported the propositions and indicate that the number of management choices considered in the timber harvest scheduling model is probably a more important factor influencing the optimal harvest schedules than is land classification.

Timber harvest scheduling in a fuzzy decision environment

1992 ◽  
Vol 22 (4) ◽  
pp. 423-428 ◽  
Author(s):  
B. Bruce Bare ◽  
Guillermo A. Mendoza
Keyword(s):  
Linear Programming ◽  
Objective Function ◽  
Deterministic Model ◽  
Programming Model ◽  
Timber Harvest ◽  
Harvest Scheduling ◽  
Fuzzy Decision ◽  
Decision Environment ◽  
Objective Function Values ◽  
Scheduling Models

Linear programming is a widely used tool for timber harvest scheduling in North America. However, some potential problems related to infeasible harvest schedules, overly optimistic objective function values, and the need to strictly satisfy all constraints included in deterministic model formulations have been raised. This paper describes a fuzzy approach for explicitly recognizing the imprecise nature of the harvest flow constraints usually included in harvest scheduling models. The objective function and selected constraints are viewed as soft, and satisfactory solutions are derived and discussed for several scenarios. An illustrative sample problem is presented to demonstrate the methodology, and a comparison with solutions derived from a traditional linear programming model is presented.

scholarly journals Harvest scheduling with spatial aggregation for two and three strip cut system under shelterwood management

2011 ◽  
Vol 57 (No. 6) ◽  
pp. 271-277 ◽  
Author(s):  
M. Konoshima ◽  
R. Marušák ◽  
A. Yoshimoto
Keyword(s):  
Spatial Aggregation ◽  
Decision Variable ◽  
Scheduling Problem ◽  
Harvest Scheduling ◽  
Aggregation Method ◽  
Management Units ◽  
Decision Variables ◽  
Optimal Harvest ◽  
Cutting System ◽  
Sequential Cuts

We propose a spatial aggregation method to solve an optimal harvest scheduling problem for strip shelterwood management. Strip shelterwood management involves either a two-cut system with a preparatory-removal cut cycle, or a three-cut system with a preparatory-establishment-removal cut cycle. In this study we consider these connected sequential cuts as one decision variable, then employ conventional adjacency constraints to seek the best combination of sequential cuts over space and time. Conventional adjacency constraints exclude any spatially-overlapped strips in the decision variables. Our results show the proposed approach can be used to analyze a strip shelterwood cutting system that requires "connectivity" of management units.

Optimal harvest scheduling at the forest level in the presence of the risk of fire

1986 ◽  
Vol 16 (2) ◽  
pp. 266-278 ◽  
Author(s):  
W. J. Reed ◽  
D. Errico
Keyword(s):  
Dynamic Equations ◽  
Scheduling Problem ◽  
Deterministic Approach ◽  
Harvest Scheduling ◽  
Forest Harvest ◽  
Timber Supply ◽  
Reasonable Approximation ◽  
Optimal Harvest ◽  
The Impact ◽  
Scheduling Models

The effect of fire on forest yields has been well documented in stand-level analyses; however, forest-level effects are less widely known. A set of dynamic equations can be constructed that describe the evolution of a forest under the impact of harvesting and random fire. When fire is treated in a deterministic fashion, these equations can be used to formulate an optimal harvest scheduling problem that can be solved using linear programming. Examples using white spruce data for the Fort Nelson Timber Supply Area of British Columbia show that even modest rates of fire can have a dramatic impact and that present harvest scheduling models may be considerably overestimating projected forest harvest levels. Results also show that the deterministic approach appears to be a reasonable approximation of the true stochastic fire problem.

Optimal harvest scheduling in Eucalyptus plantations

2009 ◽  
Vol 11 (8) ◽  
pp. 548-554 ◽  
Author(s):  
Luis Diaz-Balteiro ◽  
Mercedes Bertomeu ◽  
Manuel Bertomeu
Keyword(s):  
Harvest Scheduling ◽  
Optimal Harvest ◽  
Eucalyptus Plantations

Application of Honey-Bee Mating Optimization to Naphtha Reforming Reactor

2013 ◽  
Vol 11 (1) ◽  
pp. 293-308 ◽  
Author(s):  
Somayeh Karimi ◽  
Navid Mostoufi ◽  
Rahmat Sotudeh-Gharebagh
Keyword(s):  
Objective Function ◽  
Honey Bee ◽  
Process Model ◽  
Global Optimum ◽  
Inlet Temperature ◽  
Local Optimum ◽  
Naphtha Reforming ◽  
Decision Variables ◽  
Algorithm Comparison ◽  
Honey Bee Mating Optimization

Abstract Modeling and optimization of the process of continuous catalytic reforming (CCR) of naphtha was investigated. The process model is based on a network of four main reactions which was proved to be quite effective in terms of industrial application. Temperatures of the inlet of four reactors were selected as the decision variables. The honey-bee mating optimization (HBMO) and the genetic algorithm (GA) were applied to solve the optimization problem and the results of these two methods were compared. The profit was considered as the objective function which was subject to maximization. Optimization of the CCR moving bed reactors to reach maximum profit was carried out by the HBMO algorithm and the inlet temperature reactors were considered as decision variables. The optimization results showed that an increase of 3.01% in the profit can be reached based on the results of the HBMO algorithm. Comparison of the performance of optimization by the HBMO and the GA for the naphtha reforming model showed that the HBMO is an effective and rapid converging technique which can reach a better optimum results than the GA. The results showed that the HBMO has a better performance than the GA in finding the global optimum with fewer number of objective function evaluations. Also, it was shown that the HBMO is less likely to get stuck in a local optimum.

scholarly journals OPTIMIZATION OF B-SERIES PROPELLER DESIGN AS KCR 60 PROPULSOR TO ACHIEVE OPTIMAL PERFORMANCE USING MATHEMATICAL MODEL

JOURNAL ASRO ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 83
Author(s):  
Akhmat Nuryadin ◽  
Abdul Rahman ◽  
Cahyanto Cahyanto
Keyword(s):  
Objective Function ◽  
Area Ratio ◽  
Diameter Ratio ◽  
Decision Variable ◽  
Propeller Design ◽  
A Value ◽  
Decision Variables ◽  
Blade Area ◽  
Calculation Results ◽  
Constraint Variable

The process of designing a propeller as a ship propulsor is an important step to produce a propeller that has the ability to achieve the desired target speed of the ship. Propeller optimization is an effort to produce a propeller design with optimal capabilities. This propeller design uses a B-series propeller where this propeller is commonly used as ship propulsor. Optimization steps to find the optimal propeller, namely: determining the objective function, determining the decision variable, and determining the constraint variable. The objective function of this optimization is to determine the Advanced-optimal (J-opt) coefficient value for the propeller. The J-opt coefficient must have a value greater than the J-Design coefficient (J-d) value and the smallest possible value (minimization function). For decision variables include picth diameter ratio (P / D) and Blade area ratio (Ae / Ao) and number of leaves (Z). While the constraint variables are: the pitch diameter ratio value of the B-series propeller (0.5≤P/D≤1.4), the blade area ratio B-series (0.3≤Ae/Ao≤1, 05) as well as the number of blade (2≤Z≤7). From the calculation results of the optimization of the B-series propeller design for the KCR 60, the optimum value is different for each blade. the propeller with the number of blade 2 (Z = 2) obtained the optimum propeller with the value of J-opt =0.77098733, Ae/Ao=0.3, P/D=1.13162337, KT = 0.165632781, 10KQ=0, 27546033 and efficiency=0.73198988. Popeller with number of blades 3 (Z=3) obtained optimum propeller with J-opt value=0.77755594, Ae/Ao=0.3, P/D=1.06370107, KT=0.168069763, 10KQ=0.28984068 and efficiency=0.70590799. Propeller with number of blades 4 (Z=4) obtained optimum propeller with J-opt value=0.78478688, Ae/Ao=0.45954773, P/D=1.03798312, Kt=0.172147709, 10Kq= 0.3091063 and efficiency=0.67797119. Propeller with blades number 5(Z=5) obtained optimum propeller with J-opt value=0.78575616, Ae/Ao=0.65607164, P/D=1.02716571, KT=0.174099168, 10KQ=0.31376705 and efficiency=0.67547177. Propeller with blades number 6 (z=6) obtained optimum propeller with J-opt value=0.78867357, Ae/Ao=0.71124343, P/D=1.0185055, KT=0.176525247, 10KQ=0.32215257 and efficiency =0.66705719. Propeller with number of blades 7 (Z=7) obtained optimum propeller with J-opt value=0.7949898, Ae/Ao=0.69772623, P/D=1.01780081, KT=0.181054792, KQ=0.34011349 , and efficiency =0.64804328.Keywords : KCR, Optimization,Wageningen B-series.

scholarly journals Cable Tension Analysis Oriented the Enhanced Stiffness of a 3-DOF Joint Module of a Modular Cable-Driven Human-Like Robotic Arm

2020 ◽  
Vol 10 (24) ◽  
pp. 8871
Author(s):  
Kaisheng Yang ◽  
Guilin Yang ◽  
Chi Zhang ◽  
Chinyin Chen ◽  
Tianjiang Zheng ◽  
...  
Keyword(s):  
Objective Function ◽  
Optimization Model ◽  
Human Robot Interaction ◽  
Robotic Arm ◽  
Robot Interaction ◽  
Cable Tension ◽  
Tension Distribution ◽  
Stiffness Model ◽  
Redundantly Actuated ◽  
Objective Function Values

Inspired by the structure of human arms, a modular cable-driven human-like robotic arm (CHRA) is developed for safe human–robot interaction. Due to the unilateral driving properties of the cables, the CHRA is redundantly actuated and its stiffness can be adjusted by regulating the cable tensions. Since the trajectory of the 3-DOF joint module (3DJM) of the CHRA is a curve on Lie group SO(3), an enhanced stiffness model of the 3DJM is established by the covariant derivative of the load to the displacement on SO(3). In this paper, we focus on analyzing the how cable tension distribution problem oriented the enhanced stiffness of the 3DJM of the CHRA for stiffness adjustment. Due to the complexity of the enhanced stiffness model, it is difficult to solve the cable tensions from the desired stiffness analytically. The problem of stiffness-oriented cable tension distribution (SCTD) is formulated as a nonlinear optimization model. The optimization model is simplified using the symmetry of the enhanced stiffness model, the rank of the Jacobian matrix and the equilibrium equation of the 3DJM. Since the objective function is too complicated to compute the gradient, a method based on the genetic algorithm is proposed for solving this optimization problem, which only utilizes the objective function values. A comprehensive simulation is carried out to validate the effectiveness of the proposed method.

Forest neighbourhoods for timber harvest scheduling

1994 ◽  
Vol 70 (6) ◽  
pp. 768-772 ◽  
Author(s):  
Rick A. Wightman ◽  
Emin Z. Baskent
Keyword(s):  
Forest Management ◽  
Data Model ◽  
Timber Harvest ◽  
Spatial Modelling ◽  
Harvest Scheduling ◽  
Vector Data ◽  
Further Development ◽  
Vector Data Model ◽  
Stand Conditions ◽  
Small Forest

Forest management involves exploring through time the scheduling opportunities for timber and non-timber values within a forest. The ability to identify and form neighbourhoods — areas of suitable stand conditions and locations — is critical to this endeavour. This paper presents a GIS-based algorithm for identifying and forming forest neighbourhoods suitable for timber harvest scheduling. The resulting neighbourhoods are contiguous and overlapping, composed of stands sharing similar attributes. Similarity is based on a definable similarity list where stand conditions closest to one another in the list are most similar to one another. The algorithm is demonstrated with a single stand example and then a small forest example. Control of neighbourhood size is limited using a vector data model, except in forests composed of small stands. The examples illustrate that neighbourhood inclusion is dependent on both a forest stand's condition and relative position in the forest. The paper concludes with suggestions for further development of the algorithm. Key words: timber harvest scheduling, forest management, spatial modelling, GIS, neighbourhoods

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