APPLICATION OF LINEAR GOAL PROGRAMMING TO FOREST HARVEST SCHEDULING

Resource /Energy Economics and Policy,

A COMPARISON OF OBJECTIVE FUNCTION STRUCTURES USED IN A RECURSIVE GOAL PROGRAMMING-SIMULATIONS MODEL OF FARM GROWTH

Research Methods/ Statistical Methods,

A REVIEW OF APPLICATIONS OF MULTIPLE - CRITERIA DECISION-MAKING TECHNIQUES TO FISHERIES

Management of public resources, such as fisheries, is a complex task. Society, in general, has a number of goals that it hopes to achieve from the use of public resources. These include conservation, economic, and social objectives. However, these objectives often conflict, due to the varying opinions of the many stakeholders. It would appear that the techniques available in the field of multiple-criteria decision-making (MCDM) are well suited to the analysis and determination of fisheries management regimes. However, to date, relatively few publications exist using such MCDM methods compared to other applicational fields, such as forestry, agriculture, and finance. This paper reviews MCDM applied to fishery management by providing an overview of the research published to date. Conclusions are drawn regarding the success and applicability of these techniques to analyzing fisheries management problems.Resource /Energy Economics and Policy,

Separating Agent-Functioning and Inter-Agent Coordination by Activated Modules: The DECOMAS Architecture

The embedding of self-organizing inter-agent processes in distributed software applications enables the decentralized coordination system elements, solely based on concerted, localized interactions. The separation and encapsulation of the activities that are conceptually related to the coordination, is a crucial concern for systematic development practices in order to prepare the reuse and systematic integration of coordination processes in software systems. Here, we discuss a programming model that is based on the externalization of processes prescriptions and their embedding in Multi-Agent Systems (MAS). One fundamental design concern for a corresponding execution middleware is the minimal-invasive augmentation of the activities that affect coordination. This design challenge is approached by the activation of agent modules. Modules are converted to software elements that reason about and modify their host agent. We discuss and formalize this extension within the context of a generic coordination architecture and exemplify the proposed programming model with the decentralized management of (web) service infrastructures

Production planning under dynamic product environment: a multi-objective goal programming approach

Production planning is a complicated task that requires cooperation among multiple functional units in any organization. In order to design an efficient production planning system, a good understanding of the environment in terms of customers, products and manufacturing processes is a must. Although such planning exists in the company, it is often incorrectly structured due to the presence of multiple conflicting objectives. The primary difficulty in modern decision analysis is the treatment of multiple conflicting objectives. A formal decision analysis that is capable of handling multiple conflicting goals through the use of priorities may be a new frontier of management science. The objective of this study is to develop a multi objective goal programming (MOGP) model to a real-life manufacturing situation to show the trade-off between different some times conflicting goals concerning customer, product and manufacturing of production planning environment. For illustration, two independent goal priority structures have been considered. The insights gained from the experimentation with the two goal priority structures will guide and assist the decision maker for achieving the organizational goals for optimum utilization of resources in improving companies competitiveness. The MOGP results of the study are of very useful to various functional areas of the selected case organization for routine planning and scheduling. Some of the specific decision making situations in this context are: (i). the expected quality costs and production costs under identified product scenarios, (ii).under and over utilization of crucial machine at different combinations of production volumes, and (iii). the achievement of sales revenue goal at different production volume combinations. The ease of use and interpretation make the proposed MOGP model a powerful communication tool between top and bottom level managers while converting the strategic level objectives into concrete tactical and operational level plans.

Application of Multiple Criteria Decision Models for Oilseed Crops in Pakistan’s Punjab

Pakistan is deficient in major food products. Self-sufficiency in food has virtually always been a major priority, because imports of wheat, edible oil, sugar, pulses and milk products put a massive burden on the balance of payments for the country. The increase in the production of oilseed has been a priority goal of the agricultural development policy in Pakistan. The oilseed crops have been validated as alternative crops on several target locations of different agro-ecological zones [PARC (1990)]; but the success of this validation work in terms of their dissemination is very limited. The possibility of including these crops in well established systems needed to be well conceived. The selection of farming systems, which have the potential to adopt such crops, is a prerequisite to investigate the problems and prospects of oilseed crops. The emphasis of the study is, therefore, on the identification of typical farm situations where the oilseed crops can be evaluated for their potential inclusion in the cropping plans. A real decision-making environment in agriculture involves several objectives along with their explicit targets.

Behavioral networks as a model for intelligent agents

On-going work at NASA Langley Research Center in the development and demonstration of a paradigm called behavioral networks as an architecture for intelligent agents is described. This work focuses on the need to identify a methodology for smoothly integrating the characteristics of low-level robotic behavior, including actuation and sensing, with intelligent activities such as planning, scheduling, and learning. This work assumes that all these needs can be met within a single methodology, and attempts to formalize this methodology in a connectionist architecture called behavioral networks. Behavioral networks are networks of task processes arranged in a task decomposition hierarchy. These processes are connected by both command/feedback data flow, and by the forward and reverse propagation of weights which measure the dynamic utility of actions and beliefs

Process Planning Based on User Preferences

Typical approaches to adaptive slicing in previous literature have typically used surface finish requirements to control the slicing process. As a result, slice schemes improve the part's surface quality, but do not enable explicit trade-offs between finish and build time. The purpose of this article is to present a process planning method that enables the preferences of the user for surface finish, build time, and accuracy to control how trade-offs are made in a process plan. A multiobjective goal formulation is used by this method to evaluate how well user preferences are met by a process plan. This method consists of three modules, for determining part orientation, for slicing the part, and for determining other parameter values. An example with several scenarios representing different user preferences is provided to illustrate the process planning method.Mechanical Engineerin