Jeff R. Wright

A multiobjective integer programming model for the land acquisition problem

Abstract The purpose of this paper is to present a multiobjective integer programming formulation for the analysis of the land acquisition problem. There are two important contributions of this paper. First, the model incorporates the discrete and multiobjective nature of land acquisition. Second, we present an efficient, specialized algorithm for finding non-inferior solutions of a multiobjective integer program, a problem for which a general-purpose algorithm, applicable to moderately sized problems, does not exist.

Expert Systems: applications to urban planning

***e FACHGEBIET*** Mathematical Geology, Computer Applications, Artificial Intelligence, Urban Economics and Regional Economics ***INTERESSENTENGRUPPE*** Of interest to Urban and Regional planners, civil engineers, geographers; computer scientists; operations researchers; landscape architects; and advanced students in the above disciplines.- Level: Technical Book, Monograph ***URHEBER*** T.J. Kim, University of Illinois, Champaign, IL; L.L. Wiggins, Massachusetts Institute of Technology, Cambridge, MA; J.R. Wright, Purdue University, Lafayette, IN (Eds.) ***TITEL*** Expert Systems: Applications to Urban Planning ***BIBLIOGRAPHISCHE-ANGABEN*** 1990. XIV, 268 pp. 48 figs. Hardcover DM 78, - ISBN 3-540-97171-8 ***LANGTEXT*** While expert systems have become a popular topic in the computing, medical and engineering fields, the expert system is still a new technology in urban planning. This book introduces expert systems for problem solving in urban planning and describes the way in which heuristic knowledge and rules of thumb of expert planners can be represented through computer programs. The book presents practical applications of expert systems for solving many important urban planning problems, particularly those issues that many practicing planners face in their daily operations. Problems and issues discussed are grouped in the following categories: - Land Use Planning - Transportation Planning - Site Selection and Analysis - Environmental Planning - Conflict Mediation and Legal Disputes - Future Developments and Directions Expert Systems: Applications to Urban Planning will benefit both urban planners who wish to learn how this new technology might be applied to their daily work as well as researchers in expert systems seeking new ideas for systems design.

Discrete event sequencing as a Traveling Salesman Problem

Abstract Though many complex sequencing problems can be formulated as a Traveling Salesman Problem (TSP), the technique is not commonly employed for computational reasons. This research provides a novel perspective on the use of this methodology to the problem of steel product sequencing through the milling process of a large manufacturing facility. The purpose of this paper is to show how more traditional heuristic scheduling procedures may be restructured as TSP problems of manageable size and with significant improvement in attainment of production objectives. Modern steel production facilities are composed of many interrelated processes. The conventional approach to improving overall plant efficiency is to devise optimal operating strategies for each separate process. One such process, scheduling steel bars through the hot strip mill, is shown to lend itself well to optimization techniques when formulated and solved as the well-known Traveling Salesman Problem. Initial results on actual production schedules are shown to compare well with other scheduling techniques; improving efficiency by as much as 78% in total schedule penalty.

Optimal inter-process steel production scheduling

Abstract Optimal scheduling of production through the hot strip mill of a steel manufacturing facility is characterized by multiple and conflicting objectives. A production strategy designed to achieve maximum product quality may be expensive and cumbersome in terms of overall throughput while a strategy that achieves high volume production may sacrifice product quality. By considering the hot strip mill as an isolated production facility, a “just in time delivery” scenario can be modeled as a goal program. With experience, the goal programming model can be calibrated to simulate the decision of those experts responsible for developing the production schedule making mill operations more consistent and cost effective.

Shape considerations in spatial optimization

Abstract The land allocation problem is one of selecting, from a set of available land units or parcels, a subset of units displaying certain desirable characteristics or having special morphology. Several discrete programming models are presented for the problem of allocating an area of land for development when the shape of the resulting land area is a primary concern. The solution procedure is shown to be satisfactory for small to medium sized problems and can accommodate simple (rectangular) shapes.

An implicit enumeration technique for the land acquisition problem

Abstract The effect of geometrical changes of symmetric rigid-jointed portal frames on their natural frequencies is analysed. Discussed are the following issues: (a) the sensitivity of the frequencies to selected shape variables; (b) the variation of the three lowest frequencies ω1, ω2 and ω3 as functions of the shape variables in a prescribed domain; and (c) the occurrence of the repeated lowest frequency ω1.

Probabilistic Inferencing and Spatial Decision Support Systems

The premise behind the use of formal land use allocation models is that certain geographical regions are better suited for specific facilities and land uses than other geographical regions. The goal of land allocation models is to generate good strategies for the assignment of specific land use activities to the most suitable available land units, based on appropriate measures of suitability. As distinguished from the widely-studied facility location models that treat optimal locations as points in a plane or along a network, land use allocation models treat optimal locations as two-dimensional areas.

Drought contingency planning

Abstract Simulation gaming has the potential to enhance the effectiveness of drought management planning. The Indianapolis water supply system is used to illustrate how. First, the probability of experiencing a severe drought in Indianapolis is examined using historical streamflow data. The effects of such a drought on the municipal water supply system are then analysed using a recently developed simulation model of the Indianapolis water system. Consideration is given to the water resource decision-making problems that might arise under drought conditions, along with a discussion of the benefits of employing simulation gaming in the analysis of these problems. A basic outline for the design of a drought management simulation exercise is presented.

Microcomputer Implementation of SANTA: A Personnel Management Model

The focus of this research was the implementation of the computer-based personnel management model known as SANTA; for Systematic Analysis of Noninferior Transfer Assignments. The model is a multiobjective integer program that can generate the complete and precise tradeoff curve between the objectives of minimizing total distance that the reassigned workforce must travel from their respective homes to one of many site locations, and minimizing the maximum distance that any one worker must travel. System constraints include demand requirements for workers at each site and the limited availability of state-owned vehicles that may be issued to workers assigned to remote sites. Details of the model structure and solution procedure are presented together with the results of an actual application. A complete users guide for model operation is provided as an appendix to this report.

A multi-objective model for seasonal personnel reassignment

Abstract The focus of this research was the development of a model to address the problem of reassigning summer construction workers to winter snow and ice removal teams in an efficient and cost-effective manner. The model is a multi-objective integer program that can generate the complete and precise trade-off curve between the objectives of minimizing total distance that the reassigned workforce must travel from their respective homes to one of many site locations, and minimizing the maximum distance that any one worker must travel. System constraints include demand requirements for workers at each site and the limited availability of state-owned vehicles that may be issued to workers assigned to remote sites. Details of the model structure and solution procedure are presented together with the results of an actual application.