Holon Academic
Institute of
Technology
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)‫ט כ נ ו ל ו ג י ח ו לו ן (ע " ר‬
DEPARTMENT OF COMPUTER SCIENCES
‫מחלקה למדעי המחשב‬
DEVELOPMENT OF COMPUTER INTEGRATED MANUFACTURING SYSTEMS
(CIM) #60702
Semester Bet, 2005
Lecturer: Prof. Eugene Levner
LECTURE 1
Part 3.
Example of the Semestral Project.
Computer-aided design and analysis of artificial reefs
in the Eilat Gulf.
The following chapters are recommended:
CHAPTER
EVALUATION
Part 1 General Description of the Project
20 %
1. General features of modern AR in Israel in the
world
2. Basic requirements to AR in Eilat Gulf
(defense, water cleaning, research, seabeach
protection, coral reef protection, etc.) and
characteristics.
3. Full informal description of the problem
5%
4. Survey of relevant literature or Internet
sources (abstracts of at least 2 sources)
Part 2. Formal Modeling and Algorithms
5%
1. Formal description of the design problem
as
a
multi-criteria
mathematical
programming problem (variables plus
constraints plus criteria) and attributeranking problem
2. Description of a multi-criteria MP
algorithm and attribute-ranking Borda
algorithm
3. Choosing and description of the chosen
softeware (LINDO, STORM, GAMS, etc.)
4. Computer programming (in addition to
using GAMS, Storm, etc.)
Part 3.. Practical Computations
1. Collection of real data and maps
2. Experimental computing and statistics
3.Comparison of several variants of reef
structures and locations
4. Results and conclusions
5. Defense of the project
Total
03-502-6733
5%
5%
Maximum 30%
Maximum 10%
Maximum 10%
Maximum 10%
Maximum 10 %
50%
10%
10%
10%
10%
10%
20+30+50+5 (bonus) =105 nikudot
:'‫ פקס‬,03-502-6731 :'‫ טל‬,58102 ‫ חולון‬,305 ‫ ת"ד‬,52 ‫רח' גולומב‬
52 Golomb St., Holon 58102 Israel. Tel: 972-3-502-6731, fax: 972-3-502-6733 http://www. cteh.ac.ll
Abstract
This project is devoted to the computer-aided analysis and the design of a structure of multifunctional artificial marine structures (AMSs) including artificial reefs (ARs). Any form of the AMS
construction will have ecological, technological and economic risks associated. What is of a special
interest for this project, is the fact that the AMS may affect the associated risks in two opposite
directions: on the one hand, they decrease certain risk types and, at the same time, they may increase
some other associated risks. The project defines the spectrum of potential risks and the range of
corresponding advantages and disadvantages owned by the AMS. We consider the computer model
of a risk-minimization CAD in terms of multi-criteria decision trees and multi-criteria linear
programming permitting to find the optimal structure of the AMS.
‫הערכת סיכוים סביבתיים ואופטימיזציה של מבנים ימים מלאכותיים רב‬
‫ברירתיים‬
‫אקולוגים מנוגדים אשר מופיעים‬-‫( סוציאו‬effects) ‫חלק זה של פרויקט מוקדש ללימוד של אפקטים‬
‫ כל צורה של‬.‫בעיצוב ויצור של מערכות ימיות מלאכותיות )ממ”י ( הכוללות בתוכם שוניות מלאכותיות‬
‫ מה שמושך את תשומת ליבנו בפרויקט הזה‬.‫ טכנולוגים וכלכליים‬,‫ממ”י מלוווה בסיכונים אקולוגים‬
‫הינה עובדה שממ”י יכולים לגרום מצד אחד לגידול סיכונים מסויימים ומצד שני להביא לצימצום של‬
.‫סיכונים אחרים‬
.‫אנו מגדרים את הרשימה של סיכונים אפשריים וגם רשימת יתרונות וחסרונות הרלוונטים‬
‫בסוף הפרק הזה בונים מודל מתמטי לבעית צימצום סיכון בעזרת כלים תכנות ליניארי רב קריטריוני‬
‫( המאפשר למצוא מבנים אופטימליים של מערכות ימיות‬multi-criteria linear program)
.‫מלאכותיות‬
1. Introduction
The potential use of artificial reefs (AR) as a tool in coastal management is well described in
the literature (see, e.g., [1-12], and numerous references therein). Among many perspective
directions of potential use of the ARs, and, more generally, of Artificial Marine Structures
(AMS), we may synthesize the main ones, as follows:
 ecosystem protection and maintenance of biodiversity [1-3],
 coastal zone protection, including protection of beach and historical sites [4,5],
 human health care, including monitoring sea water quality and creating better
conditions for tourism and recreational diving,
 enhancement of fishing yields, and
 improvement of biological and environmental research and education.
According to [9], the main reasons for creating marine protecting areas and AMS are: marine
environment protection (93% of research papers are devoted to this aspect), biodiversity
maintenance and tourism promotion (67% of papers), and fisheries maintenance (53%);
research and education are secondary objectives.
In the USA, hundreds of public artificial reefs are now constructed annually, using a
combination of Federal, State, local government and private funds. For the year 2000-2001
an estimated US$700,000 was spent on artificial reef construction in Florida only. Since
1996, the project component of the state reef programme has been level funded with
US$300,000 in Federal Aid and US$300,000 in Saltwater Fishing License revenues. A 1992
study of a single artificial reef in Lorain County, Ohio (on Lake Erie) estimated the
economic value generated by the reef during that year to be US$275,000 [5, 11].
Holon Academic
Institute of
Technology
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DEPARTMENT OF COMPUTER SCIENCES
‫מחלקה למדעי המחשב‬
Over 50% of artificial reef programmes worldwide, however, have failed due to poor site
selection, inadequate planning, a lack of monitoring, or because no proper management was
put in place according to a set of suitability criteria (salinity, currents, depth), on the basis of
biological, socio-ecological and hydrodynamic modeling [1, 3, 5].
This part of the project is devoted to the study of social and ecological contradicting effects
related to the design, construction, and maintenance of multi-functional AMSs and ARs. The
main attention is given to the comparison and analysis of contradicting positive and negative
effects related to the operation of AMSs in exploited marine ecosystems and finding optimal
decisions related to the location, size, structure, maintenance and operation of artificial reefs
aimed to minimize the evolved environmental risks and maximize the advantages of AMSs
for the regional mariculture and the environment.
2. Integrated Management of AMS and Risks
Any form of the AMS construction will have ecological, technical and economic risks
associated [2-5, 11]. What is of a special interest for our research, the AMS may affect the
associated risks in two opposite directions: they decrease some risk types and, at the same
time, they may increase some other associated risks. In what follows, we define the
spectrum of potential risks and the problems experienced by the regional mariculture and
economics. Specifically, the risks which have greatest impact on human health, the
biodiversity and the environment will be focused upon. Namely, five main classes of risks
related to the AMSs will be studied:
1. Risk of the loss in biodiversity, the loss of habitat and associated species;
2. Risk (danger) of beach erosion and destroying the eco-equilibrium.
3. Risk (danger) for the human health, including aspects related to water quality,
recreational diving and tourism;
4. Risk for fisheries yield, and, the last but not least,
5. Risks related to the decrease in the quality of environmental research and education.
On the one hand, invariably, there will be a loss of habitat and associated species as well as
a disturbance to an equilibrium in an ecosystem when a large-size AMS is placed on to the
seabed, and so we can observe the negative aspect of the ARstructure. However, many
species will adapt and take advantage of opportunities available, the environmental factors
will influence the type of species that can live in the new environment and therefore the
habitat may alter, thus leading to a new ecological equilibrium.
A similar ambiguous situation is with the risk related to beach erosion and the equilibrium of
the marine ecosystem. On the one hand, for AR, an associated technical risk representing its
(un)safety and technical unreliability is to be estimated; moreover, the unpredictable nature
of the marine environment is to be taken into account in these estimations. Mistakes,
inaccuracy and ignorance in the technical risk estimations can lead to the construction
failures; as a consequence, disastrous AMS construction projects of the past, unfortunately,
can be named [1, 5]. On the other hand, the AMS can considerably mitigate the risk of beach
erosion and promote a (new) equilibrium of a marine ecosystem. The project will produce an
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52 Golomb St., Holon 58102 Israel. Tel: 972-3-502-6731, fax: 972-3-502-6733 http://www. cteh.ac.ll
accurate risk estimate in order to identify those positive protective functions of the AMSs
and to find their optimal effectiveness.
The same kind of arguments is related to the risk for the human health: on the one hand, an
artificial reefs may increase the carrying capability of the marine ecosystem and, thus,
improve the sea water quality water but, on the other hand, the risk of water and fish
contamination by toxic materials of which AMSs are done should be taken into account. In
this case, again, the trade-off between the positive and negative factors for the human health
is to be accurately estimated by using modern econometric and computer tools.
Advantages and drawbacks of the AMS related to fishery and mariculture production are
evident and fully recorded in the literature (see [1-6], among many others).
Our main assumption, which we intend to test and verify, is that the positive role of the
AMSs can be more significant, both from the biological, ecological and social points of
view, than the negative one. Moreover, the AR structures can be designed to optimise the
fishery capabilities, to increase the carrying capability of the marine ecosystem, to decrease
sea water pollution and to promote sustainable development of regional fishery industry and
beach economy (tourism, surfing, etc).
A main objective of the research done in this part of the project is the design and use of new
mathematical and computer models providing optimal engineering and ecological
performance of MARs. Our study will focus on the development and analytical comparison
of two possible mathematical techniques:
 Multi-criteria mathematical (deterministic and stochastic) programming [13];
 Decision trees, and
 Fuzzy and interval-valued analysis and optimization [14, 15].
It is thought that the following main parameters are worth considering during this stage of
the project:
 Location - mimic the biological, geographical and economic environment the MARs will
be placed in;
 Length and size of artificial reefs;
 Materials and structure of artificial reefs, minimizing the toxic effects;
 Consider the needs of the organisms;
 Consult local organisations, residents and authorities in respect with the aesthetics
requirements.
Particular interest is being paid to finding optimal decisions (locations, sizes, structures of
the AMSs) that could benefit the economical and social life of the region, including:
 feeding commercially important species, such as crabs, lobsters and fish;
 decreasing sea water pollution;
 monitoring and control of beach erosion;
 decreasing risks for the human health related to water and beach pollution.
The following advantages of artificial reefs leading to possible mitigation of environmental
risk will be taken into account in the proposed econometric and computer models (the list
will be extended and detalized at the second stage of the project):
(a)




HABITAT PROVISION
small fish
shell fish
marine vegetation
lobsters, olsters, etc.
Holon Academic
Institute of
Technology
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(b) COASTAL PROTECTION

dissipate wave energy

reduce beach sand losses

create wider beach salient

increased protection of sea wall in stormy weather

protect pier from wave energy .
(c ) ECONOMICS BENEFITS
 benefits for fishery and aquaculture
 tourism attraction
 attract more visitors to the area (divers, surfers, etc.)
(d) SOCIAL AND POLITICAL BENEFITS
 benefits for the human health
 sport and recreation benefits, especially for young people
 international cooperation, in particular in the Eilat-Aqaba Marine Park
 ARs open new doors within the regional coastal zone management and promote a
healthier, more sustainable environment.
To summarize, this part of the project is to aimed to justify, by using computer simulation
and theoreic econometric models, that the multi-functional artificial reefs represent a new
phase in sustainable technology, by offering a solution to the problems of coastal defence,
whilst providing benefit to local economies through amenity and habitat enhancement.
2.1. Integrated Management of AMS: Main Definitions
Following the definitions for integrated management of marine ecosystems given in [13, 17],
we choose the following, perhaps somewhat utopian, vision of the objectives of integrated
management of artificial marine structures and, in particular, artificial reefs:
 To identify all AMS user groups and to carefully analyze socio-economic, political,
organizational and other interactions and inter-links between them. coastal, marine
and terrestrial activitiescoordinate competing interests of all AMS users: all user
groups must be identified by and to efficiently design allocate water resources
through thorough coordination of social values, and environmental costs, factors and
benefits.
 To coordinate and resolve conflicts among the AMS user groups by including all
units of government, agencies and AMS stakeholders in the decision-making
process.
 To promote ecosystem conservation and biodiversity maintenance.
 To enhance good sea water quality according to national and international standards.
 To foster public health and safety.
 To mitigate the environmental risks caused by AMS misuse and water pollution.
03-502-6733
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52 Golomb St., Holon 58102 Israel. Tel: 972-3-502-6731, fax: 972-3-502-6733 http://www. cteh.ac.ll
There are many definitions of environmental risk [13, 17]. Speaking informally, the
environmental risk is a quantitative measurement of ecological hazards with their economic,
social and related consequences being taken into account. Following the U.S. EPA
definition of ecological risk assessment [17], we define environmental risk assessment as a
quantitative appraisal of the actual or potential impact on humans, animals, plants and
technological infrastructures of contaminants from a hazard.
Before the risk assessment is explained formally and in more detail, let us define the terms
hazard and risk – how we understand them in the present work. Hazard is the potential for
harm. For example, one type of the hazard is defined by the fact that the sea waters may be
polluted by an AMS materials; a hazard here is the danger for human health. Other possible
types of hazards are enlisted below:
 Danger for small fish,
 Danger for shell fish,
 Danger for marine vegetation,
 Danger for lobsters, olsters, etc.,
 Danger to coral reefs and other natural resources,
 Danger of beach sand losses,
 Danger of beach erosion and beach pollution,
 Danger of sea waves and stormy weather,
 Danger for fishery and mariculture industries,
 Danger for the tourism industry,
 Danger for divers, surfers and other beach visitors, etc.
Ecological risk is the likelihood of harm occurring in an ecosystem and the severity of its
outcome. There are many ways in which the evaluation of risks can be carried out [13].
These range from the numerically complicated systems to a qualitative expert judgment of
risk, that is, {low, medium or high}. Most of the formal ways define risk R as the product of
the weight w of a hazard (also called a risk factor) and amount of damage, Q caused by the
hazard, in a monetary, or material, or grade form: R = wQ.
A risk factor (also called a risk weight, or a risk factor number) is the product of the
likelihood (probability) and severity of harm arising from a hazard. A likelihood rating is
based on the qualitative scale shown below.
1. Not likely. There is really no likelihood of an accident or pollution occurring. Only
under freak conditions could there be a possibility of an accident or illness. All
reasonable precautions have been taken so far as is reasonably practicable. This
should be the normal state of the water source.
2. Possible. If other factors were present, a pollution or illness might occur, but the
probability is low and the risk is minimal.
3. Quite possible. The accident or pollution may happen if additional factors precipitate
it, but it unlikely to happen without them.
4. Likely.
5. Very likely. If the situation continues as it is, there is almost a 100% certainty that an
accident or pollution will happen at least once.
Now let us establish a severity rating for the identified hazards using the following scale:
1. Nil. No risk of injury, or contamination, or disease
2. Slight. Causing minor injury or harm.
3. Moderate. Causing moderate injury, or harm, or disease.
4. High. Causing death or serious injury to an individual.
5. Very high. Causing multiple deaths and/or widespread illnesses to population.
Holon Academic
Institute of
Technology
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‫מחלקה למדעי המחשב‬
A risk factor number is obtained by multiplying the likelihood rating by the severity rating.
A number between 1 and 25 would result. Such a rating enables the most serious risks to be
considered first, i.e. the higher the number the higher the risk.
We will classify the risk factor number as follows:
 16 – 25
Extreme
Risk level unacceptable.
 10 – 16
High
Undesirable.
 7 – 10
Medium
May be acceptable.
 1–6
Low
May be acceptable.
In our example considered above,
stressors, may be presented as
the risk to human health caused by several toxic
R = wW = j=1,…,L wj(Wj)Wj,
where:
L : the number of stressors, fons et origo of water pollution;
wj = wj(Wj): the risk factor number for the jth stressor;
Wj : the amount of the harm caused by the jth stressor.
3. Mathematical Model
This section outlines the mathematical form of a risk minimization model in terms of
multi-criteria mathematical programming problem. (For the sake of simplicity of the
presentation, the costs are not considered and real-life data are absent).
Notation
Risk classes and subclasses.
Five risk classes:
BD: Risk of the loss in biodiversity, the loss of habitat and associated species;
BE: Risk (danger) of beach erosion and destroying the eco-equilibrium.
HH: Risk (danger) for the human health, including aspects related to water quality,
recreational diving and tourism;
FY: Risk for fisheries yield, and, the last but not least,
EE: Risks related to the decrease in the quality of environmental research and education.
Twelve risk subclasses.
 SmF: Risk to diversity and long-term viability for small fish,
 ShF: Risk for shell fish,
 MF: Risk for marine vegetation,
 LO: Risk for lobsters, olsters, etc.,
 CR: Risk for coral reefs,
 NR: Risk for other natural resources,
 BS: Risk of beach sand losses,
 EP: Risk of beach erosion and beach pollution,
 SW: Risk of sea waves and stormy weather,
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52 Golomb St., Holon 58102 Israel. Tel: 972-3-502-6731, fax: 972-3-502-6733 http://www. cteh.ac.ll
 FM: Risk for fishery and mariculture industries,
 TI: Risk for the tourism industry,
 BV: Risk for divers, surfers and other beach visitors.
Indices
i = risk subclasses, i = 1,… , I =12.
j = stressor, j = 1,…, J.
k = option of location of a AMS, k= 1,… , K.
s = option of length and size of a AMS, s =1, …, S.
m = option of material and structure of a AMS, s =1, …, M.
n = a variant of an AMS chosen n  ( k × s × m ) , n = 1, …, N =K×S×M.
Variables
 Lij Location variable: Lij =1, if the jth option of location is chosen, and Lij =0, otherwise.
 Sij Size variable: Sij =1, if the jth option of length and size is chosen, and Sij =0,
otherwise.
 Mij Material variable: Mij =1, if the jth option of material and structure is chosen, and Sij
=0, otherwise.
 xij selection variable: xij =1, if the dth variant of an AMS is chosen, and xij =0,
otherwise.
Parameters
ADdj : Amount of stressor j imposed by the dth variant of an AMS chosen.
ABdj : Amount of benefit b imposed by the dth variant of an AMS chosen.
MWdj : Maximum allowed amount of stressor j,
Bi :
Maximum available amount of resource r used for establishing an AMS.
Qf: Total quantity of beneficial properties obtained as a result of establishing an AMS.
Constraints
The first group of constraints state that the total amount of biological, social and ecological
benefits expected as a result of establishing an AMS must satisfy the corresponding
demand:
(1)
Bdj = i=1,…, I ABdj xijd = BDdj, for all d, f and j.
The second set of constraints state that the total amount of hazards originating from the
establishing of an AMS should not exceed the maximum allowed norm:
(2)
Hdj = i=1,…, I ADdj xijd ≤ MWdj, for all d, f and j.
The third set of constraints state the bounds on the material, financial, human and othr
resources required for the establishment of an AMS:
(3)
j=1,…, 5d=1,…, D QFijd xijd ≤ Bi, for all i .
The fourth set bound to the total amount of most dangerous subclasses of risks:
(4)
i=1,…, I d=1,…, D QFijd ≤ Rj, for all j .
Multiple Criteria
Rj = d=1,…,D wd QWdj (j=1,…, J): Ecological risk of the jth subclass defined above.
Problem Formulation
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MINIMIZE Rj = d=1,…,D wdQWdj (j = 1,…, 5):
subject to constraints (1)-(4) above.
For solving that multiple-criteria optimization problem, we proceed with a standard minmax approach [14], according to which we find a solution providing the minimum value to
MAX (Rj│ j=1,…, J) subject to constraints (1)-(4). Thus, we reduced a multi-criteria
problem to a standard single-criterion integer programming problem.
3. Conclusion and Directions for Further Research
A multi-criteria decision-making approach is developed that opens up fresh opportunities for
minimizing ecological risks and coordinating technological, economic, social and ecological
contradictory demands of different users of artificial marine structures. The suggested
mathematical model and interactive computer-aided solution procedure directs conflicting
interests to a compromise and cooperative utilization of available resources. The choice of
weights for different risk classes and priorities of participating players as well as extensive
practical computational experiments on real-life data are to be done at the next stage of the
project.
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52 Golomb St., Holon 58102 Israel. Tel: 972-3-502-6731, fax: 972-3-502-6733 http://www. cteh.ac.ll
Survey,
OCS
Study,
MMS
www.id.ucsb.edu:16080/lovelab/Report.html)
2001-028
(see
also
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solution. Ecol. Econ., 31, 287-404
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14. Levner E., et al., , 1993, Modern Mathematical Methods of Optimization, Akademie
Verlag, Berlin, 416 pp.
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Hull, Quebec, Canada, ISBN 0-662-34457.
17. USA EPA, Ecological Risk Assessment Guidance for Superfund, USA Environmental
Protection Agency, PA, 1991.
1
)'‫ מ‬10 ‫מצוף (עומק‬
‫ צפים‬AMS
)'‫ מ‬12 ‫(עומק‬
AMS
‫אריחי קרמיקה צמודי‬
)'‫ מ‬20 ‫קרקעית (עומק‬
‫ צמוד קרקעית‬AMS
)'‫ מ‬20 ‫(עומק‬
' ‫ מ‬15 ‫מרוחקים עד‬
‫מהמתקן‬
‫מ כ ו ן‬
‫א ק ד מ י‬
‫‪Holon Academic‬‬
‫‪Institute of‬‬
‫‪Technology‬‬
‫ט כ נ ו ל ו ג י ח ו לו ן (ע " ר)‬
‫מחלקה למדעי המחשב‬
‫‪2‬‬
‫‪DEPARTMENT OF COMPUTER SCIENCES‬‬
‫‪ AMS‬צמוד קרקעית (עומק ‪ 20‬מ')‬
‫מנשאים לאריחי‬
‫קרמיקה ‪ 100X20‬ס"מ‬
‫אריחי קרמיקה‬
‫‪ 20X20‬ס"מ‬
‫צינורות פוליאטילן‬
‫בקוטר ‪ 25‬ס"מ‬
‫בטון יצוק‪-‬‬
‫דופן ‪ 15‬ס"מ‬
‫‪ 130‬ס"מ‬
‫משקל משוער‪ 2.5 -‬טון‬
‫‪ 120‬ס"מ‬
‫דחיית מים ‪ 850 -‬ק"ג‬
‫‪ 130‬ס"מ‬
‫‪ AMS‬צפים (עומק ‪ 12‬מ')‬
‫רח' גולומב ‪ ,52‬ת"ד ‪ ,305‬חולון ‪ ,58102‬טל'‪ ,03-502-6731 :‬פקס'‪:‬‬
‫‪03-502-6733‬‬
‫‪52 Golomb St., Holon 58102 Israel. Tel: 972-3-502-6731, fax: 972-3-502-6733 http://www. cteh.ac.ll‬‬
Example of an artificial reef