Approaches to integrated strategic/tactical forest planning

Traditionally forest planning is divided into a hierarchy of planning phases. Strategic planning is conducted to make decisions about sustainable harvest levels while taking into account legislation and policy issues. Within the frame of the strategic plan, the purpose of tactical planning is to schedule harvest operations to specific areas in the immediate few years and on a finer time scale than in the strategic plan. The operative phase focuses on scheduling harvest crews on a monthly or weekly basis, truck scheduling and choosing bucking instructions. Decisions at each level are to a varying degree supported by computerized tools. A problem that may arise when planning is divided into levels and that is noted in the literature focusing on decision support tools is that solutions at one level may be inconsistent with the results of another level. When moving from the strategic plan to the tactical plan, three sources of inconsistencies are often present; spatial discrepancies, temporal discrepancies and discrepancies due to different levels of constraint. The models used in the papers presented in this thesis approaches two of these discrepancies. To address the spatial discrepancies, the same spatial resolution has been used at both levels, i.e., stands. Temporal discrepancies are addressed by modelling the tactical and strategic issues simultaneously. Integrated approaches can yield large models. One way of circumventing this is to aggregate time and/or space. The first paper addresses the consequences of temporal aggregation in the strategic part of a mixed integer programming integrated strategic/tactical model. For reference, linear programming based strategic models are also used. The results of the first paper provide information on what temporal resolutions could be used and indicate that outputs from strategic and integrated plans are not particularly affected by the number of equal length strategic periods when more than five periods, i.e. about 20 year period length, are used. The approach used in the first paper could produce models that are very large, and the second paper provides a two-stage procedure that can reduce the number of variables and preserve the allocation of stands to the first 10 years provided by a linear programming based strategic plan, while concentrating tactical harvest activities using a penalty concept in a mixed integer programming formulation. Results show that it is possible to use the approach to concentrate harvest activities at the tactical level in a full scale forest management scenario. In the case study, the effects of concentration on strategic outputs were small, and the number of harvest tracts declined towards a minimum level. Furthermore, the discrepancies between the two planning levels were small

Collision-free inverse kinematics of a 7 link cucumber picking robot

The paper presents results of research on inverse kinematics algorithms to be used in a functional model of a cucumber harvesting robot consisting of a redundant manipulator with one prismatic and six rotational joints (P6R). Within a first generic approach, the inverse kinematics problem was reformulated as a non-linear programming problem and solved with a generic algorithm. Solutions were easily obtained, but the considerable calculation time needed to solve the problem prevented on line implementation. To circumvent this problem, a second, less generic approach was developed consisting of a mixed numerical-analytic solution of the inverse kinematics problem exploiting the particular structure of the P6R manipulator. This approach facilitated rapid and robust calculation of the inverse kinematics of the cucumber harvester. During the early stages of the cucumber harvesting project, this inverse kinematics algorithm was used to off-line evaluate the ability of the robot to harvest cucumbers using 3D-information of a cucumber crop obtained in a real greenhouse. Thereafter, the algorithm was employed successfully in a functional model of the cucumber harvester to determine if cucumbers were hanging within the reachable workspace of the robot and to determine a collision-free harvest posture to be used for motion control of the manipulator during harvesting

Spatial optimization for land use allocation: accounting for sustainability concerns

Land-use allocation has long been an important area of research in regional science. Land-use patterns are fundamental to the functions of the biosphere, creating interactions that have substantial impacts on the environment. The spatial arrangement of land uses therefore has implications for activity and travel within a region. Balancing development, economic growth, social interaction, and the protection of the natural environment is at the heart of long-term sustainability. Since land-use patterns are spatially explicit in nature, planning and management necessarily must integrate geographical information system and spatial optimization in meaningful ways if efficiency goals and objectives are to be achieved. This article reviews spatial optimization approaches that have been relied upon to support land-use planning. Characteristics of sustainable land use, particularly compactness, contiguity, and compatibility, are discussed and how spatial optimization techniques have addressed these characteristics are detailed. In particular, objectives and constraints in spatial optimization approaches are examined

Collision-free inverse kinematics of the redundant seven-link manipulator used in a cucumber picking robot

The paper presents results of research on an inverse kinematics algorithm that has been used in a functional model of a cucumber-harvesting robot consisting of a redundant P6R manipulator. Within a first generic approach, the inverse kinematics problem was reformulated as a non-linear programming problem and solved with a Genetic Algorithm (GA). Although solutions were easily obtained, the considerable calculation time needed to solve the problem prevented on-line implementation. To circumvent this problem, a second, less generic, approach was developed which consisted of a mixed numerical-analytic solution of the inverse kinematics problem exploiting the particular structure of the P6R manipulator. Using the latter approach, calculation time was considerably reduced. During the early stages of the cucumber-harvesting project, this inverse kinematics algorithm was used off-line to evaluate the ability of the robot to harvest cucumbers using 3D-information obtained from a cucumber crop in a real greenhouse. Thereafter, the algorithm was employed successfully in a functional model of the cucumber harvester to determine if cucumbers were hanging within the reachable workspace of the robot and to determine a collision-free harvest posture to be used for motion control of the manipulator during harvesting. The inverse kinematics algorithm is presented and demonstrated with some illustrative examples of cucumber harvesting, both off-line during the design phase as well as on-line during a field test

A Buffer Stocks Model for Stabilizing Price of Commodity under Limited Time of Supply and Continuous Consumption

Staple foods, in developing countries especially in Indonesia, have extremely volatile among harvest and planting season caused by inelastic of supply-demand and price disparity. When a staple food is shortage in market, it will trigger crisis of economics, political and social because it concerns with food security. This paper develops a buffer stock model for stabilizing price of commodity under limited time of supply and continuous consumption. The performance criterion of model will consider financial loss of producer, consumer and government side when market is interfered by price-stabilization program and price-support program simultaneously. The price fluctuation will be stabilized by market operation where buffer stocks are bought from domestic and import supply point. This paper provides a price band policy that attempts to bound domestic price variation between a set of upper and lower bounds on the level of domestic prices. We consider three sets of problems reflecting different three prices elasticity from 4 period of supply and demand. Numerical examples are found to be consistent with empirical estimates regarding the relationship price elasticity with price band and with government budget for the agenda of assisting household to assure availability a staple food with enough amounts at rational prices. Keywords: buffer stocks, price band, stabilization, limited time of supply, staple foods

BUFFER STOCK MODEL FOR STABILIZING PRICE WITH CONSIDERING THE EXPECTATION STAKEHOLDERS IN THE STAPLE-FOOD DISTRIBUTION SYSTEM

The extremely different supplies between the harvest season and the planting season are one of serious problem in the staple-food distribution system. In free-market mechanism, this extreme difference will trigger price-volatility and shortage of staple-food. This situation causes opportunity-losses for the stakeholders (producer, consumer, agent and government) in the staple-food distribution system. The government has got incurred losses because the government cannot achieve food-security for the households. The government has several price stabilization policies; one of them is market intervention policy by using buffer stock schemes to stabilize price and to reduce losses for the stakeholders. The objective of this research is to determine the buffer stock schemes required for market-intervention program. In the previous researches, the buffer stock models have been developed separately based on optimization and econometrics methods. Optimizations methods have been used to determine the level of availability with schemes consist of time and quantity of buffer stock. Econometrics methods have been used to determine the equilibrium price by using the selling-price and the amount of buffer stock. In this research, the integration of optimization model (multi-objectives programming) and econometrics model are used to develop a buffer stock model with the decision variables that consist of quantity, time, and price. Key Words: Buffer Stock Model, Market-Intervention, Price-Stabilizatio