An operational, spatially constrained harvest scheduling model

1990 ◽  
Vol 20 (9) ◽  
pp. 1438-1447 ◽  
Author(s):  
Stephen E. Clements ◽  
Patrick L. Dallain ◽  
Mark S. Jamnick
Keyword(s):  
Monte Carlo ◽  
New Brunswick ◽  
Timber Harvest ◽  
Programming Algorithm ◽  
Search Procedure ◽  
Harvest Scheduling ◽  
Short Term ◽  
Mapping Strategy ◽  
Scheduling Model

A Monte Carlo integer programming algorithm was developed to generate short-term (25-year), spatially feasible timber harvest plans for a New Brunswick Crown license. Solutions for the short-term plan are considered feasible if they meet spatial and temporal harvest-flow and adjacency constraints. The solution search procedure integrates a randomly generated harvesting sequence and checks of harvest-flow and adjacency constraints. The model was used to determine the annual allowable cut under three constraint formulations. The three formulations represented increasing levels of adjacency constraints, from no constraints to levels similar to current provincial requirements. The annual allowable cut under the most strict constraint formulation was reduced by 9% from the unconstrained formulation, for a given mapping strategy of a long-term harvest schedule. These applications of the model indicate that it is suitable for spatially constrained harvest scheduling on Crown licenses in New Brunswick.

Spatial and temporal allocation of stratum-based harvest schedules

1993 ◽  
Vol 23 (3) ◽  
pp. 402-413 ◽  
Author(s):  
Mark S. Jamnick ◽  
Karl R. Walters
Keyword(s):  
New Brunswick ◽  
Programming Model ◽  
Timber Harvest ◽  
Short Term ◽  
Manual Task ◽  
Potential Losses ◽  
Operational Activities ◽  
Reproducible Manner ◽  
Small Forest

Stratum-based timber harvest schedules must be disaggregated into operational plans prior to implementation. In most cases this is an expensive and time-consuming manual task that does not ensure consistency between the long-term harvest schedule and short-term operational activities. This paper presents the results of applying the CRYSTAL algorithm, which automates the disaggregation and allocation of a stratum-based harvest schedule into harvest blocks, to a small forest in New Brunswick. The results indicate that it is possible to use a set of allocation guidelines to quickly delineate harvest blocks in a consistent, reproducible manner. We also discuss how the algorithm is used in conjunction with a Monte Carlo integer programming model to estimate the potential losses in timber harvest volumes attributable to deviations from the stratum-based schedule and the addition of adjacency constraints.

Economic trade-offs of managing forests for timber production and vegetative diversity

1994 ◽  
Vol 24 (6) ◽  
pp. 1260-1265 ◽  
Author(s):  
David N. Holland ◽  
Robert J. Lilieholm ◽  
David W. Roberts ◽  
J. Keith Gilless
Keyword(s):  
Diversity Index ◽  
Basal Area ◽  
Timber Harvest ◽  
Forest Stand ◽  
Timber Production ◽  
Harvest Scheduling ◽  
Scheduling Model ◽  
Trade Offs ◽  
Compositional Diversity ◽  
Shannon’S Diversity Index

Three indices of forest stand structural and compositional diversity were incorporated into a linear programming timber harvest scheduling model to examine the trade-offs between managing stands for timber production and biodiversity objectives. The indices, based on Shannon's diversity index, characterized stand species diversity, basal area diversity, and vertical crown diversity. While harvest-level objectives were often compatible with the maintenance of vegetative diversity, the maximization of present net value was accompanied by substantial reductions in all three measures of diversity.

Evaluation of two risk mitigation strategies for dealing with fire-related uncertainty in timber supply modelling

2010 ◽  
Vol 40 (6) ◽  
pp. 1136-1154 ◽  
Author(s):  
David W. Savage ◽  
David L. Martell ◽  
B. Mike Wotton
Keyword(s):  
Risk Mitigation ◽  
Timber Harvest ◽  
Fire Regimes ◽  
Mitigation Strategies ◽  
Planning Model ◽  
Harvest Scheduling ◽  
Scheduling Model ◽  
Risk Mitigation Strategies ◽  
Harvest Volume ◽  
Forest Managers

We embedded a linear programming timber harvest scheduling model into an aspatial stochastic simulation model of a flammable forest to evaluate two fire risk mitigation strategies. The harvest scheduling model is solved repeatedly to produce harvest schedules within a rolling planning horizon framework. The risk mitigation strategies we examined were (1) whether or not to account for fire in the planning model and (2) replanning interval. We evaluated those strategies under four representative fire regimes. We found that accounting for fire in the planning model reduced the harvest volume variability as fire activity increased (i.e., for average annual burn fractions ≥0.45%), but replanning intervals over a range of 1 to 10 years had little impact on harvest volume variability. We also developed a risk analysis decision-making aid that forest managers can use to help deal with fire-related uncertainty. Our results suggest that risk-averse forest managers should account for fire while planning, especially when burn fractions exceed 0.45%.

scholarly journals SEQUENTIAL CAPITAL INVESTMENT DECISION MAKING UNDER EXTREME CASH FL OW SITUATIONS: EVIDENCE USING MONTE CARLO SIMULATION

2015 ◽  
Vol 16 (5) ◽  
pp. 877-900 ◽  
Author(s):  
Wenqing Zhang ◽  
Prasad Padmanabhan ◽  
Chia-Hsing Huang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Capital Investment ◽  
Net Present Value ◽  
Capital Budgeting ◽  
Cash Flows ◽  
Present Value ◽  
Short Term ◽  
Value Analysis

Uncertainty influences a decision maker's choices when making sequential capital investment decisions. With the possibility of extremely negative cash inflows, firms may need to curtail operations significantly. Traditional Net Present Value analysis does not allow for efficient management of these problems. In addition, firm managers may behave irrationally by accepting negative Net Present Value projects in the short term. This paper presents a Monte Carlo simulation based model to provide policy insights on how to incorporate extreme cash flows and manager irrationality scenarios into the capital budgeting process. This paper presents evidence that firms with irrational managers and experiencing extremely negative cash flows may, under certain conditions, reap long term rewards associated with the acceptance of negative Net Present Value projects in the short term. These benefits are largest if cost ratios (discount rates) are small, or investment horizons are high. We argue that acceptance of short term negative Net Present Value projects implies the purchase of a long term real option which can generate positive long term cash flows under certain conditions.

Improved Immune Algorithm for Hydrothermal Joint Economic Scheduling

2014 ◽  
Vol 1030-1032 ◽  
pp. 2582-2585
Author(s):  
Wei Zhou Wang ◽  
Gang Zhang ◽  
Yu Li ◽  
Jing Jing Zheng
Keyword(s):  
Large Scale ◽  
Optimization Problem ◽  
Considerable Proportion ◽  
Reservoir Capacity ◽  
Short Term ◽  
Hydrothermal Scheduling ◽  
Scheduling Model ◽  
Scale Optimization ◽  
Hydropower Construction

China is in a period of rapid economic development, Hydropower construction scale is increasingly expanding, Hydropower accounts for a considerable proportion of the grid, therefore it becomes more important to conduct the hydrothermal joint economic scheduling in gird. Hydrothermal joint scheduling optimization can make water fire and electric play to their strengths and so that to make a great contribution on conserving energy and protecting the environment. Medium and long-term hydrothermal scheduling seems to be more important because its long scheduling period, and can guide the short-term hydrothermal operation. However, under the medium and long-term hydrothermal scheduling, time span and the changing range of reservoir capacity is big, respect to short-term joint scheduling it is a more complex large-scale optimization problem. Therefore, it is very important to establish a reasonable medium and long-term hydrothermal joint scheduling model within the accuracy range and study the corresponding algorithm.

Share repurchases: analyzing short-term and long-term wealth effects

2019 ◽  
Vol 45 (3) ◽  
pp. 430-444
Author(s):  
John Rozycki ◽  
Inchul Suh
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Numerical Model ◽  
Wealth Effects ◽  
Share Repurchases ◽  
Share Repurchase ◽  
Long Term Effects ◽  
Short Term ◽  
Content Type

PurposeThe purpose of this paper is to examine the short-term and long-term wealth effects of two share repurchase motivations.Design/methodology/approachThe authors use a multi-period numerical model and a Monte Carlo simulation. The Monte Carlo simulation introduces uncertainty into firms’ market values and eliminates some restrictions used in the numerical model.FindingsIn the long term, firms that refrain from repurchasing overvalued shares outperform otherwise identical firms that do not exhibit such restraint. In the short term, firms that repurchase overvalued shares can outperform firms that refrain from such repurchases. Total returns are a function of misvaluation, the firm’s repurchase decision, the rate of return on invested cash and how long the shares remain misvalued. Share price volatility can influence share repurchase decisions.Research limitations/implicationsThe models are incapable of fully modeling the complexities of a dynamic economic environment.Practical implicationsManagers and investors need to be aware of the short-term and long-term effects of share repurchases. Additionally, investors can gain insight into a firm’s share repurchase motivation by observing its cash balances over time.Social implicationsShare repurchases are a zero-sum game with potentially different short-term and long-term wealth effects.Originality/valueWhen studying the wealth effects of share repurchases, it is important to consider the motivations for repurchasing shares as well as the short-term and long-term effects.

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