Tang Loon Ching
Chong Fen Sin
Lau Boon Hwee
M. A. Quaddus
A questionnaire was designed and sent to all the members and a response rate of 30.3%
The model generates patients by specialty, medical condition and class preference.
Rules used to assign beds to patients are based on hospital policies and practices.
If no beds are found, the model puts the patients on a queue until beds become available.
When beds become available, transfers are carried out for patients who were not given
their preferred classes initially.
The model was designed and calibrated using data collected over a two-month period.
Several performance measures, e.g. bed occupancy and number of transfers, were
measured and compared with actual results. This was to ensure that the model correctly
reflect actual conditions at the hospital.
Mohammed A Razzaque
Tan Thiam Soon
This paper seeks to provide an introductory pedagogical review of this growing area
of Structured Modeling. In addition, it will also review the ongoing current research
work and highlight the opportunities for further work in this area. The objective of
the paper is to propagate Structured Modeling within the MS/OR community in our region,
with a view to stimulating research in this growing area, and leading hopefully to the
adoption and application of this tool to enhance the effectiveness of our managers.
We concentrate on the economic aspects of how an organisation should decide when
to replace its vehicles. Sometimes a replacement is made on other grounds, such as
changed technical specifications or considerations of reliability or prestige.
These must remain the responsibility of managerial policy and are not considered
in this report.
The paper first describes the theory of replacement and defines 2 replacement
policies - group replacement and individual replacement. This is followed by
an application of the theory to a department with a large fleet of vehicles.
Chew Kim Lin
Ong Hoon Liong
Chong Fen Sin
Yap Kim Yew
M. A. Quaddus
Ong-Tan Yoke Yin
The company planned to set up a FMS testing and fixing facility,
automating many of the testing functions to reduce labour cost and
increase productivity. A simulation study was condicted to identify
the most appropriate configurations, and furthermore to optimise the
most preferred configuration to achieve the planned production
Initially, the time slots for each day are ranked according to
lecturers' favoritism, the algorithm then produces time-tables with
uniform total rank score for each lecturer. With the method, special
requirements are pre-assigned manually. The computer then matches
elements in two sets, M and F, where each element of M consists of
a string of information on a lecturer, a class/group, and a teaching
activity; while each element of F is made up of a string of
information on facility and time available. The matching is done
so as to ensure that each time-table obtained in solution has about
the same total rank score.
The heuristic algorithm also takes care of the constraints. The given
list of constraints are weighted according to the order of importance.
By means of the method, more than one timetable may be produced for
each lecturer with different violation scores to the constraints.
It terminates when an acceptance score is reached.
In our dual-based heuristic, several features have been incorporated
into the efficiency and consistency of the algorithm. Three major
ones are: the modification of the generating procedures of both
dual solutions and their corresponding primal solutions, and the
introduction of a new primal interchange procedure which further
improves primal solutions at hand.
The efficiency of the algorithm was tested with some static and
dynamic location problems. The computational results were
encouraging: for the absolute majority of test problems, the
algorithm generated optimal solutions in a satisfactorily small
computation time and even for the remaining problems, the quality
of solutions generated was superior to that by the existing
dual-based solution procedure.
But, although the availability at decreasing costs of many tools,
as videographics systems, data-base systems, personal computers and
local area networks offer new chances in supporting managers for
decision making, a lot of work has to be done in order to implement
and build up effective DSS for practical application.
In this work the peculiarities and the basic structure of a DSS
are defined and the differences with respect to management
information systems, expert systems and management support systems
This paper, among the components of DSS, in particular deals with
the formalization of decisional problems, the mathematical modelling
and the structure of the models-base management system.
In order to come into practical examples, some typical decision
problems are illustrated relatively to the centralized management
of urban traffic and resources allocation in a transit company.
Finally the data-base and models-base needs relatively to these
problems are analyzed for the design of DSS at operative level.
In general, it is observed that usage of sophisticated capital
budgeting techniques has increased among business enterprises
in the US, Europe and elsewhere. Discounted cash flow techniques,
in particular, are used more and more by large companies. In South
East Asia, however, empirical evidence on the state of practice
in capital budgeting is almost non-existent. In an attempt to fill
the gap in knowledge, a survey was conducted in October 1983 to
study the extent of usage of various capital budgeting techniques
and the management of capital expenditure activities in Malaysian
The analysis is based on responses from 66 companies listed in
the Kuala Lumpur Stock Exchange with significant annual capital
expenditures in the years 1981-1982. An important finding of the
survey is that payback period, degree of necessity or urgency,
accounting rate of rate (ARR), internal rate of return (IRR),
net present value (NPV), profitability index (PI), and net
future value (NFV) are, in that order, the most frequently
used methods of appraising capital investment proposals. Most
companies used multiple techniques when evaluating major capital
expenditures. Use of discounted cash flow (DCF) methods is a
relatively recent phenomenon, with two-thirds of the DCF users
adopting the method only within the last five years. The interest
rates most commonly used in DCF methods are target yield for new
investments, cost of capital plus risk factor, and cost of long
term debt plus risk factor. In three-quarters of the companies,
formal proposals and profitability analysis are required for most
projects. Market prospects, competition and political risk are
perceived to be the most significant factors affecting the companies'
capital expenditure decisions. Most companies compute cash flows
after deducting either interest, or interest and tax, or interest,
tax and dividend; whereas, risk is mainly accounted for by shortening
the payback period and setting a high IRR for acceptance.
The 1983 survey also looked into various matters relating to the
administration of capital expenditure activities. It was observed
that nearly all responding companies were undertaking active and
systematic search for alternatives to their major investment
proposals. Three-quarters of the companies carried out long-range
planning, with a three to five years horizon, with respect to their
capital expenditure. Nearly 80 percent of the companies have
performed a post-completion audit but these exercises had largely
been financial reviews conducted by their accounting departments.
The capital budgeting activities in about half of the companies
are supported by their computer-based information systems.
Operations Research has been used as an aid to capital budgeting
decision making but the results of its usage are quite uncertain
at this point in time. Generally, the respondents ranked
industry-specific information to be more relevant and important
than general macroeconomic information in their capital budgeting
As a final analysis, the responding companies are found to fall into
three clusters and can be conveniently grouped as those with annual
capital expenditures less than M$1 million, between M$1 million and
M$10 million, and more than M$10 million. The sophistication of the
capital budgeting techniques employed are then analysed with respect
to these three groups of companies. The results are also discussed
in the context of a three-stage model of the capital budgeting
Senior executive decision-making (predominantly discretionary) and
strategic Corporate support depends on proper DSS implementation
strategies and well defined control processes.
This paper discusses the above delineation of benefits and their
impacts in light of an implementation at ICL Asia Pacific Pty Limited
Headquarters in Sydney.
Executive views and perspectives on future advantages are cited in
response to the increased needs of executive support in leveraging
In contrast to the optimization problems with scalar criteria, where
in most of the cases either the optimal solution is unique or there
exist only a few ones, to the optimization problems with vector or
other non-scalar criterion, the optimal solutions form a set
containing infinite elements in general, provided that all criterion
functions are equally set to a certain extent for optimization by
increasing (or decreasing) each of their values as great as possible
and there exist no additional objective or subjective optimization
considerations. This peculiar characteristics of multicriteria
optimization problems originates in the fact that the order relation
on the set of feasible solutions of the problem is a partial ordering
in general while that of scalar criterion optimization problems is
a total one. The set of optimal solution for multicriteria optimization
problems is known as the set of efficient solutions or Pareto
In practice, in order to obtain a final optimal solution determined
uniquely, additional optimization consideration such as the preference
thinking of the decision maker must be taken into account. However,
it is evident that the final optimal solution should be an element
of the set of Pareto solutions, no matter what additional
considerations have been taken into account for choosing it. In this
sense the set of Pareto solutions forms a rational and objective
basis for the solution of multicriteria optimization problems and
thus a most important object of study in this subject.
This paper aims at giving a brief survey of recent results on the
multicriteria optimization problems of controlled dynamic systems,
which mainly includes those obtained by the author. Owing to the
fact mentioned above, the Pareto optimality will be regarded as
the underlying concept of multicriteria optimality and the
discussions will be confined to characteristics of Pareto optimal
solutions and methods of obtaining them.
Results indicated that scheduling rules have a significant effect on
system performance. Contrary to popular belief, small batch sizes have
been found to perform well when operated in association with an
appropriate priority rule. An increase in job inter-operation time
resulted in an accumulation of work-in-prgress but left machine
utilisation relatively unaffected.
As a result, decision support systems have been widely used in the
airline inductry. Coupled with the peculiar nature of the airline
business, a separate decision support association was formed: the
Airline Group of International Federation of Operations Research
This paper describes the decision support systems that have been
successfully implemented in the airline industry. Many of these
systems can also be used in other industries.
The author worked for Quantas Airways Ltd in Australia for 6 years
as Senior O.R. Analyst. In this paper, he borrowed heavily on his
experience at the company.
The set of objects to be considered is described by a relational
data base (kind of objects naturally depends on application). The
attributes of the objects are referred as the components of image
A classification method is characterized by the choice of parameters,
algorithms dealing with recoding of attributes, space metrics, and
image transformation. Elementary descriptive statistics (averages,
standard deviations, histograms, etc.) are used to improve the
The system is partially menu-driven and partially command-driven.
The image transformation and source data coding are handled by
user's own written codes which can consist of command such as
"if ...then ... else" and arithmetic and logical operations.
The system is implemented on portable PC EPSON HX-20 and written