A spatial optimisation model for multi-period landscape level fuel management to mitigate wildfire impacts

Elevated fuel loads are contributing to an increase in the occurrence of, and area burned by, severe wildfires in many regions across the globe. In an attempt to reverse this trend, fire and land management agencies are investing in extensive fuel management programs. However, the planning of fuel treatment activities poses complicated decision-making problems with spatial and temporal dimensions. Here, we present a mixed integer programming model for spatially explicit multi-period scheduling of fuel treatments. The model provides a flexible framework that allows for landscape heterogeneity and a range of ecological and operational considerations and constraints. The model’s functionality is demonstrated on a series of hypothetical test landscapes and a number of implementation issues are discussed.     

A stochastic approach to optimize Maritime pine (Pinus pinaster Ait.) stand management scheduling under fire risk. An application in Portugal

The paper discusses research aiming at the development of a management scheduling model for even-aged stands that may take into consideration fuel treatments to address the risk of wildfires. A Stochastic dynamic programming (SDP) approach is proposed to determine the policy (e.g. the fuel treatment and thinning schedules and the rotation age) that produces the maximum expected discounted net revenue. Fuel treatment activities encompass shrub cleanings. Emphasis was on combining a deterministic stand-level growth and yield model with wildfire occurrence and damage models to design a SDP network. SDP stages are defined by age and state variables include both the stand basal area and the number of years since the last fuel treatment. Fire occurrence and damage scenarios are addressed at each stage. Results from an application to Maritime pine (Pinus pinaster Ait.) stand management scheduling in Leiria National Forest, Portugal, are presented. Results suggest that the modeling strategy may help assess the impact of wildfire risk on the optimal stand management schedule. They confirm that the maximum expected discounted net revenues decreases. Further, albeit some timber may be salvaged after the wildfire, rotation age also decreases when the risk of fire is considered. Finally, they provide interesting insights about the role of thinning and fuel treatment policies in mitigating risk.     

Scheduling in a multi-processor environment with deteriorating job processing times and decreasing values: the case of forest fires

In forest fire fighting, time and effort required to control a fire increase if fire containment effort is delayed. The problem of scheduling multiple resources employed as parallel identical or non-identical processors in order to contain N≥2 fires may be tackled using the concept of deteriorating jobs. In this paper, the above problem is stated and a model is formulated, the criterion being to maximize the total remaining value of the burnt areas and a real-time synchronous heuristic algorithm is proposed. The heuristic algorithm’s efficiency was compared to real data provided by Greek Fire Corps from a severe wildfire near Athens in June-July, 2007.     

资源受限下森林火灾应急救援多目标调度优化

许多森林火灾由于救援资源受限而不能在第一时间扑灭,导致火灾扩大蔓延,进而造成更大的森林资源损失。因此,在救援资源受限情形下,如何对消防救援车辆进行合理的调度安排以快速和低成本地扑灭火灾已成为亟待解决的现实问题。本文研究了一类资源受限下森林火灾应急救援多目标调度优化问题,为该问题构建了多目标混合整数非线性规划模型,优化目标为同时最小化总灭火救援时间和救援车辆总行驶距离。为有效求解该问题,首先将上述非线性模型等价转化为线性模型。然后提出ε-约束法和模糊逻辑相结合的算法对问题进行求解。最后,以大兴安岭山发生的火灾案例和随机生成仿真算例对模型和算法有效性进行验证,结果表明所提出的模型和算法能够有效解决资源受限下森林火灾应急救援问题,并为决策者提供最优的消防调度方案。     

Forest management challenges for operational researchers

This is an overview of operational research work that has been carried out to support strategic forest management planning, short term forest planning, forest operations, and forest fire management. It identifies important unresolved problems and new challenges that could serve as a rich source of problems for both practitioners and researchers.     

MODELING REGENERATION AND PEST CONTROL ALTERNATIVES FOR A FOREST SYSTEM IN THE PRESENCE OF FIRE RISK

This paper addresses a fire and pest protection forest management modeling problem by developing a flexible model which integrates the concepts of: 1) species diversity 2) infestation of susceptible species; 3) natural regeneration and planting; 4) conversion of susceptible to non-susceptible species by planting; 5) pest protection by spraying; 6) age-specific harvesting; 7) intertemporal harvest flow policies; and 8) catastrophic loss due to fire. A linear programming (LP) model economically evaluates alternative regimes for protection spraying of susceptible forest species against insect infestations and alternative harvesting strategies which include conversion of susceptible species to non-susceptible, by planting. These strategies are evaluated subject to catastrophic loss due to fire. An iterative simulation-LP approach tests how well the deterministic model holds in a simulated stochastic environment. This validation procedure involves solving the optimization problem deterministically using average values for the fire and infestation proportions and also at each time period updating the system state by simulating the state transition for the next time period using randomly generated updates and re-solving using the updated state as the new initial condition. An optimal wood supply trajectory in a simulated stochastic environment is therefore constructed. The results from the iterative stochastic solution provide a confidence measure for the deterministic solution.     

FIRE DISTURBANCE PATTERNS AND FOREST AGE STRUCTURE

ABSTRACT. This paper investigates how the stability of forest age-distribution is related to the fire regimes. We start with the derivation of theoreticalnegative exponentialforest age-distribution, and use three models to explore the condition with which a stable age-distribution could be expected. The results suggested that a stable age-distribution could always be achieved as long as the forest age-specific mortality is constant over time, and the shape of a stable age-distribution is mainly determined by the forest age-specific mortality. However, the stability of forest age-distribution will be reduced when a small variation in the age-specific mortality is introduced. The simulation results of the possible patterns of the age-distribution under various fire regimes indicated that a variety of age-distribution curves could appear, including negative exponential and one or multiple peaks in the curves. The results suggested that a stable forest age-distribution might never be achieved if the forest landscape is subjected to large and irregular fire disturbances.     

Wildfire fuel management: Network-based models and optimization of prescribed burning

Wildfires are a common phenomenon on most continents. They have occurred for an estimated 60 million years and are part of a regular climatic cycle. Nevertheless, wildfires represent a real and continuing problem that can have a major impact on people, wildlife and the environment. The intensity and severity of wildfires can be reduced through fuel management activities. The most common and effective fuel management activity is prescribed burning. We propose a multi-period optimization framework based on mixed integer programming (MIP) techniques to determine the optimal spatial allocation of prescribed burning activities over a finite planning horizon. In contrast to the existing fuel management optimization literature, we model fuel accumulation with Olson’s equation. To capture potential fire spread along with irregular landscape connectivity considerations, we use a graph-theoretical approach that allows us to exploit graph connectivity measures (e.g., the number of connected components) as optimization objectives. The resulting mathematical programs can be tackled by general purpose MIP solvers, while for handling larger instances we propose a simple heuristic. Our computational experiments with test instances constructed based on real-life data reveal interesting insights and demonstrate the advantages and limitations of the proposed approaches.     

SUSTAINABLE FOREST MANAGEMENT FOR OPTIMIZING MULTISPECIES WILDLIFE HABITAT: A COASTAL DOUGLAS-FIR EXAMPLE

Wildlife species viability optimization models are developed to convert a given set of initial forest conditions, through a combination of natural growth and management treatments, to a forest system which addresses the joint habitat needs of multispecies populations over time. A linear model of forest cover and wildlife populations is used to form a system of forest management control variables for wildlife habitat modification. The paper examines two objective functions coupled to this system for optimizing sustainable joint species viability. The first maximizes the product of periodic joint viabilities over all time periods, focusing management resources on long-term equilibria, with less emphasis on conversion strategy. The second iteratively maximizes the minimum periodic joint viability over all time periods. This focuses management resources on the most limiting time periods, typically the conversion phase periods. Both objective functions resulted in either point or cyclic equilibria, with cycle lengths equal to minimum forest treatment ages. A third objective, based on maximizing the minimum individual species periodic viability is used to examine single species emphasis. Examples are developed through a case study of 92 vertebrate species found in coastal Douglas-fir stands of northwestern California.     

The Use of Historical Data in the Assessment of Combat Degradation

The paper both describes the method and presents the results of a study into the degradation (or reduction in effective fire) of infantrymen in defensive combat in the presence of live fire. The starting point was the trials performance of men in simulated combat, the degradation with live fire being assessed from aggregated comparisons with historical, or operational, data. Many factors may account for the variations between particular battles; this approach has successively isolated a set of eight important factors. These have allowed the variations between real battles to be reduced to no more than those found between replicated trials in simulated combat. The process has yielded new relationships for combat modelling.     

Scheduling electric power production at a wind farm

We present a model for scheduling power generation at a wind farm, and introduce a particle swarm optimization algorithm with a small world network structure to solve the model. The solution generated by the algorithm defines the operational status of wind turbines for a scheduling horizon selected by a decision maker. Different operational scenarios are constructed based on time series data of electricity price, grid demand, and wind speed. The computational results provide insights into management of a wind farm.     

Perspectives on experimental fires in Canadian forestry research

This paper offers some insights into the field approach to conducting experimental forest fires based on two decades of experience dealing with a wide variety of fuel types, burning conditions, and resultant fire behavior. The practical aspects involved in designing a study area for an experimental burning project and its successful execution are considered as well as the methods used in the measurement of physical fire characteristics, fuel properties, and fire weather elements. On the basis of this review, several impressions emerge about the possible future requirements and emphasis in outdoor forest fire behavior research involving naturally occurring fuel complexes. Finally, the conclusion is reached that there can be no substitute for actual “hands-on” experience in observing experimental fires as a basis for understanding the behavior of free-burning fires in the forest environment resulting from planned or accidental ignitions.     

Scheduling of production and logistics operations of steam production systems in food industries: a case study of the tomato processing industry

This study presents an optimization approach by mathematical modelling to support some of the main operational decisions in steam production systems with multiple industrial boilers. Decisions are related to boiler operations scheduling (start-up, warm-up and shutdown time), fuel replenishment (transportation and inventory management) and fuel composition consumed by each piece of equipment. These decisions are often taken based on practical experience of people involved, instead of any decision support tool using optimization techniques; as a consequence, unnecessary costs are likely to be incurred. The optimization approach is based on mixed integer programming and parameters experimental adjustment procedures. A case study of a large tomato processing plant in Brazil was carried out along 1 year using a 3-year database. Owing to the reasonably good outcomes achieved (annually potential savings around 10%), we consider the proposed approach as a suitable tool to support some of the key decisions in boiler scheduling and fuel logistics in steam production systems for tomato processing and other similar industries.     

TIMBER MARKETS AND FUEL TREATMENTS IN THE WESTERN U.S.

ABSTRACT. We developed a model of interrelated timber markets in the U.S. West to assess the impacts of large‐scale fuel reduction programs on these markets, and concomitant effects ofthe market on the fuel reduction programs. The linear programming spatial equilibrium model allows interstate and international trade with western Canada and the rest of the world, while accounting for price effects of introducing softwood logs to the market. The model maximizes area treated, given fire regime‐condition class priorities, maximum increases in softwood processing capacity, maximum rates of annual treatments, prohibitions on exports of U.S. and Canadian softwood logs from public lands and a fixed annual treatment budget. Results show that the loss to U.S. private timber producers is less than the gains for timber consumers (mills). States receiving more treatments when spending is not constrained by state proportions include Idaho, Montana, New Mexico and Oregon. When only the wildland‐urban interface is treated, California, Oregon and Washington receive more treatments. Utah and Colorado receive more treatments when low risk stands are included.     

A web-based workforce management system for Sainsburys Supermarkets Ltd

Labour scheduling plays an important and critical role in Sainsburys day to day operations and profitability. The integrated workforce management solution for Sainsburys is an intelligent solution for the operational deployment of human resources, integrated business forecasting, generation and calculation of workload and staff scheduling. The workforce management technology has provided Sainsburys with a fully web-based and centralised system that produces optimised schedules for all employees satisfying the forecasted demand of work with granularity of fifteen minutes. The system is configured to respect all operational and business requirements as well as employee contractual constraints. This paper introduces the workforce management solution system designed, developed and implemented for Sainsburys. We concentrate on two modelling structures, namely the work pattern model and optimisation model, and briefly discuss the optimisation process.     

Forest management models and combinatorial algorithms: analysis of state of the art

Linear Programming and Mixed Integer Linear Programs have been used for forest planning since the 60's to support decision making on forest harvesting and management. In particular, during the last two decades of forest management there has been an increased interest in spatial issues. Further, new environmental concerns, such as resource sustainability and wildlife protection, impose that increased attention be paid to activities carried out on the ground. Road building needed for access also requires spatial definiton. As a result, more complex models must be used. We discuss the issues which have led to the combinatorial nature of some main forest management problems and the solution algorithms that have been proposed for these problems, including local search heuristics, random search approaches, strengthening of mixed integer model formulations and Lagrangian relaxation. In this survey, we discuss which of the proposed approaches have been used succesfully, the advantages and shortcomings of each and what are still open research problems. This revised version was published online in June 2006 with corrections to the Cover Date.     

Scheduling patrol boats and crews for the Royal Australian Navy

The Royal Australian Navy's Patrol Boat Force carries out essential tasks in the surveillance, policing and defence of Australia's coastal waters. To help the Navy make efficient use of a new generation of boats, the authors have developed optimization procedures to schedule the activities of the boats and their crews. The procedures—embodied in a software system called CBM (‘Crews, Boats, Missions’)—use simulated annealing and specialized heuristic techniques within a multi-stage problem-solving framework. Tests show that CBM is reliable in terms of solution quality, and flexible with respect to the range of scheduling conditions applied. CBM has proved valuable to the Navy as an investigatory tool, and it is planned that it should be adapted for operational use, as part of a decision support system to aid in the ongoing management of patrol boat operations.