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The OR Society OR Insight Vol. 21 Issue 3
Applying ANP for raw material supply in Iranian paper industry Majid Azizi Natural Resources Faculty, University of Tehran mazizi@ ut.ac.ir Moharnrnad Modarres Department of Industrial Engineering, Sharif University of Technology modarres@shari£edu
Keywords: Analytic Hierarchy Process, Analytic Network Process, BOCR, paper industry
success factor, and there is a serious deficiency in the industry concerning the lack of proper planning of raw material supply.
Abstract The aim of this paper is to develop a strategic plan for selecting the best options for the supply of raw material to feed paper producing plants. The decision-making is examined within the framework of benefits, opportunities, costs, and risks (BOCR). A hierarchy is used to prioritize the BOCR, using the Analytic Hierarchy Process (AHP) ratings approach. A control hierarchy is then created and prioritized using the Analytic Network Process (ANP) to evaluate the "control criteria" of the system. There are a total of nineteen control criteria in the system and each controls a decision network evaluated using the ANP. The final synthesis of the system shows external procurement is the best choice.
In this paper, we apply AHP (Saaty, 1999) and ANP (Saaty, 2001a) as the tools for selecting the best choice in the field of raw material supply for paper producing plants in Iran. The main objective is to develop guidelines for strategic planning, based on the appropriate decisions made by adopting this approach. Development of reliable and stable suppliers needs long range planning; it is not wise to consider only short term planning which is mostly established on the basis of price and availability. In long range or strategic planning we need to consider various criteria influencing the decision. There are several alternatives for supply of raw material to paper manufacturers, including use of external resources, internal resources and a combination of both. Domestic raw materials for paper manufacturing come from different sources: forest resources; non forest resources such as poplar trees; bagasse (agricultural wastes) and waste paper. Some raw materials, such as poplar, birch trees, softwood species and long fiber pulp, are also imported from foreign sources, although at the moment importation is not significant.
Introduction There is a tremendous demand for various types of paper in Iran, and Iranian plants cannot produce sufficient output to satisfy this demand. The most important obstacle that domestic paper manufacturers are facing is inadequate raw material supply. As the research by Azizi et al. (2003) shows, the supply of raw material for wood and paper industries is a very important 3
Currently managers make only operational or short-term decisions. Essentially, they purchase raw materials which are available in the market, leaving them unable, in many cases, to procure enough raw material to meet production goals, particularly in the longer term.
By way of background, Table 1 shows the situation of active and inactive paper manufacturers in Iran with respect to utilized raw material.
Table I: Situation of paper rrralcing factories in Iran Factory
Annual nonnnal capacity(lOOO Ton)
Kinds of product
Kinds of utilized ra'W Inaterial
Portion froIn overall capacity
Wood and paper mazandaran
175
Printing ,writing and newsprint paper
Internal (forest wood + poplar) , External (long fiber pulp)
24.6
Iran wood and paper
150
Printing, writing and packing paper
21.1
Pars
105
Kaveh
35
Latif
15
Papirous
15
Printing and writing paper Printing ,writing, packing paper and card board Printing, writing and packing paper Packing paper
Internal (forest wood + poplar + waste paper, External (long fiber pulp) Internal(Bagasse+10 ng fiber pulp) Internal (waste paper)
Nowzohoor Kahrizak
5 38
Hygienic paper Packing paper
Karoon
70
Printing and writing paper
Harir Khoozestan Shargh Packing paper making Damavand packing paper making Miscellaneous packing paper making Gharb paper
15
Hygienic paper
9
Packing paper
15
Packing paper
Internal (waste paper)
2.1
15
Packing paper
Internal (waste paper)
2.1
50
---
Internal (forest wood and poplar)
(%)
Total Overall actual product capacity
14.7 4.9
Internal (waste paper)
2.1
Internal (waste paper) External (pulp) Internal (waste paper) Internal (Bagasse) External (long fiber pulp) Internal (Bagasse pulp) Internal (waste paper)
2.1 0.8 5.3 9.8
2.1 1.3
7
100 42
712 300
(Source: Commercial researches and studies organization and PPI, 1994) 4
In general, Iran is not rich in comparison to other countries with regard to forest resources. There are 1.2 million hectares of trading forests in northern Iran and the amount of wood exploitation from this area is limited. If the governmental organizations responsible for forest protection do not plan to preserve and develop the existing forests, major paper manufacturers, such as "Wood and Paper of Mazandaran" or "Iran Wood and Paper" that procure raw materials from northern forests will face serious problems in the near future (Mahdavi, 2003). Even now, "Wood and Paper of Mazandaran" imports birch and poplar species abundantly from another countries, owing to the deficiency in raw material.
The ANP is a coupling of two parts. The first consists of a control hierarchy or network of criteria and sub-criteria that control the interactions in the system under study. The second is a network of influences among the elements and clusters. The network varies from criterion to criterion and a super-matrix of limiting influence is computed for each control criterion. Finally, each of these super-matrices is weighted by the priority of its control criterion and the results are synthesized through addition for all the control criteria. The problem is studied through a control hierarchy or system of benefits, costs, opportunities, and risks. The synthesized result of the four control systems are combined by multiplying the benefits by opportunities and by costs and risks to determine the best outcome.
To address these issues, the rest of paper is organized as follows. In the next section we review the analytic network process (ANP) briefly. The elements of our ANP model, including alternatives, overall factors, the merits of benefits, costs, opportunities, risks and their control criteria are then discussed in more detail. Finally, the analysis of the results is discussed in the last section.
The following are some of the features of the ANP that distinguish it from the AHP (Saaty, 2001b): • Rather than a hierarchy, the basic structure of a network consists of clusters and nodes and logical connections between them. The judgment process is carried out by creating matrices of pair wise comparison judgments for nodes in a cluster linked to the same parent node.
The analytic network process (ANP) The Analytical Network Process (ANP), a generalization of the Analytic Hierarchy Process (AHP) method for multi criteria decision making, provides a broad framework for decision making in complicated environments. The advantage of this new theory over the AHP (Analytic Hierarchy Process) is its ability to extend to cases of dependence and feedback and generalization of the super-matrix approach. It allows interactions and feedback within clusters (inner dependence) and between clusters (outer dependence). Feedback can better capture the complex effects of interplay in human society. The ANP provides a thorough framework to include clusters of elements connected in any desired way to investigate the process of deriving ratio scales priorities from the distribution of influence among elements and among clusters.
• Sub-networks can be created for and attached to nodes in a network, and sub networks have the same structure as any network. There can be many layers of sub-networks. The sub networks at the bottom contain the alternatives of the decision. • Super matrices are created III the subnetworks and the results integrated with the higher levels of networks. ANP has been applied in numerous decision making scenarios. For example, in making decisions regarding the establishment of commercial ties with China (Saaty and Cho, 2001c), where it was concluded that Preferred
5
Normal Trade Relations (PNTR) is the best choice. A further example concerns how to make the decision on national missile defense program. The US government faced the crucial decision whether or not to commit itself to the deployment of a National Missile Defense (NMD) system. By applying an ANP model, deploying NMD surfaced as the best alternative (Saaty, 200 Id). Alikafa and Ozdemir (2003) used ANP and BOCR to determine membership as the best policy for an ED I Turkey relationship. The focus of the paper by Azis (2003) is to search for the most suitable form of RFA (Regional Financial Arrangement), the process of which involves a complex decision, having to include not just economic rationales but also political and other considerations. Poonikom et al. (2003) proposed a systematic framework using ANP for the selection of universities which offer engineering disciplines. The purpose of the study by Ilker et al. (2004) is to develop a multi criteria model of organic food marketing strategies which are believed to improve the domestic market. The Analytic Network Process is utilized to construct such a model. The elements of the marketing combination of them are defined and the interrelationships among these elements are assessed via a Delphi type group decision making procedure. Cevik et al. (2004) presents an integrated framework based on ANP and utilizing Delphi Technique to select an ERP system. Piantanakulchai (2005) applied ANP for prioritizing the potential highway alignments. In this study ANP is used as a novel approach to tackle the multi criteria highway corridor selection problem. The general structure of ANP and essential roles of stakeholders and experts were discussed in the research. Through a simple numerical example, the application of the proposed model is illustrated. It is generally believed that feeding more information to the model (or experts) would lead to better decision. The author suggests further study to interpret and investigate the effect of including more possible feedback blocks as added information to the proposed ANP model. Banai (2005) argues that there is a paucity of reviews of ANP development
applications. This paper provides a survey of recent developments of ANP with reference to applications in the realm of urban and regional planning. Fiala (2005) presents ANP model is suitable to analyze network economy. Some specific features of network economy as positive feedback, complementarily, network structure or dynamic environments are analyzed by ANP IDNP methods. The research shows a basic principle of the approach, although its results cannot be generalized. All of this suggests the usefulness of ANP within our study. In the next section we develop the model for this.
The ANP rnodel In this section, a model is developed to plan the best choice for the supply of raw materials to feed the paper industry. This model is designed within the framework of ANP. The alternatives are evaluated by the merits of benefits, costs, opportunities, and risks (BOCR).
The Alternatives There are three potential alternatives for procuring of the paper producing plants raw material. First choice is domestic the supply of raw material, the second one is importing and last choice is combination of them. The rnerits Merits of the problem are divided into benefits, opportunities, costs, and risks. Benefits are favorable and inevitable criteria, costs are unfavorable and inevitable criteria. Opportunities are possible and positive events and risks are possible and negative events. Overallfactors In this research the merits of benefits, costs, opportunities, and risks are influenced by following overall factors: • Social and cultural: divided into two factors, I) literacy and culture level; 2) population growth. 6
procurement of raw material for the plants does not damage the environment.
• Environmental factors related to l) forest reclamation; 2) wood and non wood plantation issues.
Wood and non wood plantation: plantation of wood and non wood plants, such as eucalyptus and poplar trees, bagasse, bamboos, is very helpful to decrease the deforestation with regard to supply of raw material for the industry.
• Economic factors related to economic issues. • Governmental laws and regulations related to imports.
Decreasing storage cost and increasing selling vohune: supply of suitable and high quality raw material improves the quality of the products. As a result, it increases selling volume and decreases the storage cost.
• Foreign trade regulations related to limits of exports from other countries.
Prioritizing BOeR Since benefits, opportunities, costs and risks are not equally important, it is necessary to prioritize them. The results of this, using a ratings scale, are reported in table 2.
Creation of new jobs: procurement of proper and adequate local raw material
Table 2: Priority rating for the rner-itse Benefits, Costs, Opportunities and Risks very high (1), high (0.51), ruedjum (0.252), low (0.124), very low (0.065) Foreign trade regulations (0.079) Governmental regulations (0.273) Economic (0.456) Environmental Forest reclamation (0.154)
Benefits Medium Low Very high Very high
Costs Very high Very high Medium Very low
Opportunities Very low Medium Very high Very high
Risks Very high Very high High Very low
Very high
Low
Very high
Very low
Medium
Medium
Medium
Medium
Very high
Low
High
Very Low
0.271
0.209
0.275
0.245
(0.333)
Wood and non wood plantation (0.667)
Social and cultural (0.038)
Population growth (0.25)
Literacy and cultural level (0.75) Overall priorities
Table 2 show opportunities and benefits have higher priorities than costs and risks in this decision, with priority of 0.275 and 0.271 respectively,
increases the income of the area. Furthermore, it creates new jobs and improves local employment level by absorption of more labor force. The criteria consist of two sub-criteria: increase of local income, and absorption of a local and skilled workforce.
The Control criteria Benefits, costs, opportunities, and risks are discussed in detail below.
Opportunities to tnanagers of paper producing plants or producers of the paper Econorrric growth of the area: creation of new producing plants increases the quality of
Benefits to tnanagers of paper producing plants or producers of the paper Not b ar-mfuf to the errvir-ormaerrt: 7
quality raw material lowers the quality level of products and consequently it decreases selling volume and increases storage cost of products in stock.
procured material in the favor of economic development of the area. Export possibilities: export is improved by economic development and high quality products.
Aclcnowfedgrrrerrt Iirnftarion to suppliers of external raw rrrarer-iab in case of importing essential raw material from foreign countries, it is required to accept the supplier's restriction which may results in procurement of raw material which is not necessarily proper or the best quality.
Industry expansion: by generation of proper conditions and procurement of facilities, expansion is accelerated. Investnlent attraction in future: potential of the region in terms of industry expansion makes investors interested in commissioning the industry in future.
Cutting forbidden by Gover-nnaerrts Government may stop cutting from the forests due to non-fulfillment or irregular and unwarranted utilization, resulting in production shutdowns.
Access to ISO standards: managers can get international standards (ISO) for the products via high quality production.
Delay in delivery of external raw rrrater-iah procurement of raw material from foreign countries may cause delay in delivery times due to administrative channels and customs restrictions, and in the extreme can force a plant to shut down.
Costs to 'managers of paper producing plants or producers of the paper Purchase of raw rrrater-iah the finished cost for purchasing each cubic meter of forest wood, poplar or orchard wood from their supplying sources to produce the product.
Prioritizing Criteria and Alternatives After pair wise comparisons between sub criteria for benefits, costs, opportunities and risks by ANP as well as pair wise comparisons of the criteria and choices against each other, following the above mentioned merits, the results are reported in Table 3.
Raw rrrarer-i'al transportation cost: transportation costs from raw material supply areas to the plants site.
Cusuorns dues: customs dues, in case of raw material imports. Deforestation costs: unwarranted utilization of the forests resulting in higher destruction levels.
Risks to 'managers of paper producing plants or producers of the paper Flood possibility: irregular utilization from the forests and soil erosion generation, increases the conditions for flood accidents. Decrease of selling aInount and increase of storage cost: improper supply and low
8
Table 3: Synthesized Priorities of the 19 Criteria and Sub criteria Merits
Criteria
Sub-criteria
Internal supply 0.552 0.583
External supply 0.161 0.154
Combined Supply 0.286 0.264
Benefits (0.271)
Create of working(0.13)
Increase ofloca1 income(0.523) Increase of local and skillful man force(0.477)
Not harmful to environment(0.364)
0.215
0.56
0.225
Wood and non wood plantation(0.203)
0.203
0.091
0.246
Decrease of storage and increase of selling(0.304)
0.304
0.537
0.258
0.348 0.348 0.654 0.255
0.406 0.406 0.086 0.447
0.245 0.245 0.26 0.298
Industry development(0.15)
0.418
0.335
0.247
Investment attraction in future(0.122)
0.363
0.358
0.28
Access to ISO standards(0.175) Opportunities Synthesized
0.202 0.420
0.542 0.312
0.256 0.267
Opportunities Normalized Purchase of raw materia1(0.455) Costs(0.209) Raw material transportation cost(0.129)
0.420 0.1 0.09
0.312 0.592 0.661
0.267 0.308 0.249
0.082 0.682
0.687 0.093
0.232 0.225
Costs Synthesized Costs Normalized Costs Reciprocal
0.296 0.296 0.358
0.437 0.437 0.243
0.266 0.266 0.399
Risks (0.245)
Flood possibi1ity(0.094)
0.695
0.078
0.227
Decrease of selling and increase of storage(0.24 7)
0.604
0.126
0.27
Acknowledgment limits to supp1iers(O.l27)
0.074
Cutting forbidden(0.335)
0.71
0.672 0.075
0.254 0.215
0.075
0.66
0.265
0.478
0.279
0.244
0.478
0.279
0.214
0.367
0.244 0.419
Benefits Synthesized Benefits Normalized Opportunities Economic growth of the area(0.346) (0.275) Export possibilities(0.207)
Customs costs(0.078) Deforestation costs(0.338)
Delay in deliver of external raw materia1(0.197) Risks Synthesized Risks Normalized Risk Reciprocal
As Table 3 shows, not harmful to environment (0.364), economic growth of the area (0.346), purchase of raw material (0.455) and cutting forbidden (0.335) have the highest priority in terms of criteria of benefits, opportunities, costs and risks respectively. Also, with regard to alternatives, external supply (0.406), internal supply (0.420), external supply (0.437) and internal supply (0.478) have the highest priority
terms of criteria of benefits, opportunities, costs and risks respectively.
In
To apply ANp, "Super Decision" software is used. In BOCR the following formula is used in calculations (Saaty, 2001 d): (Benefits)*(Opportunities) / (C osts )*(Risks) (1) 9
weights of choices against the above mentioned merits, the final scores are reported in Table 4.
Networks of Control Criteria Figure 1 shows the sub network under benefits which has been obtained by Super Decision Software.
As Table 4 shows the choice of external supply
Figure 1: Sub network under benefits
GJ(Q)[8J
!!l Subnet under Benefits Eile (lesign B.ssess/Compare
~ III e!i £
~omputa tions
"t", a
t:l.etworks tlelp
+ Ri5
..!.I Benefits - 101 xl
\. Criteria
I
INo hannfulon enviromrnent
'
Wood and non woodplantation
II
decrease storage and increase sell
Create working
I
Increase local income
Absorption of local & skillfullmanforce
Alternatives Internalraw materialsupply
Externalraw materialsupply
Similarly, the networks for costs, opportunities and risks can be developed.
Internal& Externalraw materialsupply
has the highest priority, and is the most suitable choice to procurement of raw material for paper producing plants. Considering the merits in decision making, external supply has the highest priority and the second and third is internal supply and combined supply, respectively.
Final Outcom.e By integration of the weights of the merits of benefits, costs, opportunities and risks and the
Table 4: Final Outcom.e for Priorities of the Alternatives
Internal supply External supply Combined supply
Benefits (0.271)
Opportunities (0.275)
Costs (0.209)
Risks (0.245)
0.348
0.42
0.358
0.214
Final Outcome Additive 0.336
0.406
0.312
0.243
0.367
0.337
0.245
0.267
0.399
0.419
0.325
10
Analysis
inevitable, being mitigated by the results of inevitable criteria (benefits and costs). As shown in Table 3 with regard to the result of risks, using internal resources has the highest priority and its rate is approximately, twice of other alternatives. However, with respect to Table 2 the weight of risks (0.245) is much more than costs (0.209). Thus, alternatives with high risks could not be selected. Final synthesis shows external resource is the best choice to procure raw material for paper producing plants. Although procurement of raw material from foreign countries has high costs to the factories, in long term planning, the advantages such as high quality products, conservation, lack of harm on environment, and avoiding deforestation rate are advantageous.
As shown in Table 2, opportunities and benefits are more important in the decision compared with costs and risks, because they have higher weight: opportunities = 0.275, benefits = 0.27l. From Table 3 it is implied that "not harmful to environment (0.364)" has the highest priority in terms of benefits. At present, one of the most important problems of the paper industry is damage to the environment. Irregular utilization of the forests, giving rise to the destruction of forests, accelerates the shortages of raw material resources for the industry. Importing raw materials can provide a solution to this. The problem stems from non-fulfillment as a result of poor plantation and reclamation planning after the utilization. Accordingly, conservation of the environment has high priority in this regard. Economic growth of the area (0.346) is the most important criterion in terms of opportunities. Owing to proper and high quality production, the area in which the plant is established will probably develop as an industrial and business region and consequently ends up with more economic growth. Economic development also improves other "opportunities" sub-criteria. "Purchase of raw material (0.455)" has the highest priority in terms of costs, because of lack of the proper raw material to produce final product. Furthermore, owing to the use of it by various wood industries demand increases and consequently, supply decreases.
Sensitivity Analysis Since there may be different judgments on the comparison of priority rates of benefits, opportunities, costs, and risks or their subcriteria, to achieve stability and compatibility of the analysis, we apply sensitivity analysis (see Saaty, 2001d). It can be shown that by increasing or decreasing the weight of one criterion the ratios of the weights of other three criteria (with respect to each other) remain unchanged, although the sum of their weights changes accordingly. For example, if the weight of benefit increases from 0.271 to 0.5, then the new weights of costs, opportunities and risks will be 0.144, 0.187 and 0.169, respectively. Although the sum of these weights is decreased to 0.5, they are proportional to the previous ones, i.e. 0.209, 0.275 and 0.245 (see Table 2.)
Cutting forbidden (0.335) by the government is an important risk. Areas of forests have been decreased by irregular and unwarranted utilization and inadequate conservation and reclamation planning in the last decade. For this reason, the risk of "cutting forbidden" will increase in future. As shown in Table 4, external supply, with the highest priority, is the most suitable choice for the industry to satisfy the need for raw materials. With regard to benefits and costs results as shown in Table 3, external supply has the highest priority. Internal supply has also the highest priority in terms of opportunities. This alternative will generate proper conditions for the plants in future, but its result is not
To perform sensitivity analysis, we apply the software developed by Saaty (200 1b). The results are illustrated by Figures 2, 3, 4 and 5. Some cases of weights changes are presented in Table 5. From Table 4, the priorities are E (external supply), I (internal supply) and C (combined supply). After changing the weights of one criterion, the priorities also change, as shown in Table 5. With respect to the table, opportunities and risks are more sensitive than benefits and costs. 11
Table 5. The results of sensitivity analysis
New Weight
Basic Weight
I, C, E
0.25
0.271
Benefits
I, E, C
0.285
0.275
Opportunities
C,I,E
0.243
0.271
Benefits
E,C,I
0.257
0.275
Opportunities
C,E,I
0.164
0.275
Opportunities
I,C,E
0.218
0.209
Costs
C,I,E
0.271
0.209
Costs
E,C,I
0.26
0.245
Risks
C,E,I
0.31
0.245
Risks
I,E,C
0.239
0.245
Risks
New Priorities
12
Criterion
Figure2: Sensitivity analysis for benefits
~ Sensitivity analysis for Super Dec... ~121[E]
Figure 3: Sensitivity analysis for opportunities
I!J Sensitivity analysis for Super Dec... ~I 0 J[R] Eile ~dit !:!elp
Eile ~dit tielp
1.0
1.0
0.9
0.9
0.8
0.8
0.7
0.7
0.6
0.6
0.5
0.5
0.4
0.4 i
0.2
0.2
0.1
0.1 0.1
0.1 0.2 0.3 0.4 0;5 0.6 0.7 0.8 0.9 1.0
I I I I I I I I I I I
0.2 0.3 0.4 0:5 0.6 0.7 0.8 0.9 1.0
Experiments
Experiments
External raw material supply
External raw material supply
Internal &External rawmaterial supply 3 Internal rawmaterial supply
Internal &External raw material supply 3
2
Internal raw material suoolv l1li
IPriority: Benefits
10.5
2
IPriority: Opportunities
13
10.5
1
Figure 4: Sensitivity analysis for costs
Figure 5: Sensitivity analysis for risks
[!J Sensitivity analysis for Super Dec..·lJl:l Jrg) ~ Sensitivity analysis for Super Dec... LJIQI[R) Ble ~dit tielp
Eile ~dit
1.0
1.0
0.9
0.9
0.8
0.8
0.7
0.7
0.6
0.6
0.5
0.5
0.2
0.2
0.1
0.1
0.1 0.2 0.3 0.4
,5 0.6 0.7 0.8 0.9 1.0
tielp
0.1
,, , , ,, ,, ,,,
0.2 0.3 0.4 0:5 0.6 0.7 0.8 0.9 1.0
Experiments Externalraw material supply
3
Internal ~ External rawmaterialsupply 1 Internal raw materialsuoolv
2
Experiments External raw material supply
Internal & External raw material supply 1 Internalraw material suppl\!
~I
IPriority:Costs
2 3
illI
10.5
IPriority: Risks
References Azizi M. , Modarres M., Amir S., Salehipour M., Doosthoseini K., (2003) "The group decision making to determine effective criteria for wood industry location (Case of study: Iran)" , International journal of Inquiry, Vol. 1, No.1, 63-96 Saaty T, (1999) Decision Makingfir Leaders, RWS Publications, 4922 Ellsworth Avenue, Pittsburgh, PA 15213. Saaty T, (2001a) Decision Making with Dependence
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and Feedback: The Analytic Network Process, RWS Publications, Pittsburgh, PA. Commercial researches and studies organization, 1994, Wood and paper book, Tehran Pulp & paper International, 1994, A miller freeman publication Mahdavi S., (2003), "Investigation on utilization of P. deltoides and E. camaldulensis for newsprint and printing paper", PH.D thesis, University of Tehran Saaty T, (2001b) Decision Making in Complex
Banai R., (2005) " Analytic Network Process: A Survey of Urban and Regional Planning Applications", Proceeding of the 8th International Symposium on the Analytic Hierarchy Process, ISAHP2005, University of Hawaii, Honolulu, USA Fiala P. (2005) " Analysis of network economy by ANP IDNP", Proceeding of the 8th International Symposium on the Analytic Hierarchy Process, ISAHP2005, University of Hawaii, Honolulu, USA
Environments, The Analytic Network Process for Decision Making with Dependence and Feedback, University of Pittsburgh. Saaty T. and Y Cho, (200lc), "The Decision by the US Congress on China's Trade Status: a Multicriteria analysis", Socio-Economic Planning Sciences, 35, 243-252, Elsevier ScienceLtd. Saaty T., (2001d) "Decision on National Missile Defense Program", The 6th International Symposium on the AHP in Bern, Switzerland. Alikafa E.P., M.S. Ozdemir, (2003) "The best policy for European Union and Turkey Relationship", Proceeding of the Seventh International Symposium on the Analytic Hierarchy Process ISAHP2003, Bali, Indonesia, pp 97-110. Azis Iwan]., (2003) "Complex Decision in the establishment of Asian Regional Financial Arrangement", Proceeding of the Seventh International Symposium on the Analytic Hierarchy Process ISAHP2003, Bali, Indonesia, pp 39-56. Poonikom, K., Chansa- ngavej, C., O'Brien, C., (2003) ''A Framework for Universities - Selection Decision using the Analytic Network Process (ANP) ", Proceeding of the Seventh International Symposium on the Analytic Hierarchy Process ISAHP2003, Bali, Indonesia, p:403-4l6. Ilker Y Topcu, Sebnem Burnaz, and Suha Urgan, (2004) "Modeling marketing strategies in organic food through analytic network process", MCDM 2004 conference, Whistler, B. C. Canada August 6-11. Cevik Sezi, Aktas Emel and Topcu Y Ilker, (2004) "Selection of an Enterprise Resource Planning System using Analytic Network Process: The case of Turkey", 20 the European Conference on Operation Research, OR and the Management of Electronic Services, July 4-7, Rhodes, Greece, Abstract book, p:87. Piantanakulchai M., (2005) ''Analytic network process model for highway corridor planning", Proceeding of the 8th International Symposium on the Analytic Hierarchy Process ISAHP2005, University of Hawaii, Honolulu, USA
Dr. Majid Azizi is an assistant professor in Wood & Paper Sciences and Industries. He obtained his PhD in Wood & Paper Sciences and Industries from University of Tehran. Prior to dissertation he was a research assistant for 9 years in Wood & Paper Sciences and Industries Department, Faculty of Natural Resources, University of Tehran. Dr Azizi has published 5 papers in journals of INJI, IranianJournal of Natural Resources and IWS. Also he has published 7 abstracts and papers in conferences proceeding of IUFRO All Division 5, 5th EURO/ INFORMS Joint International Meeting, The Seventh International Symposium on the Analytic Hierarchy Process (ISAHP), 20th European Conference on Operational Research (Euro XX), 17th International Conference on Multiple Criteria Decision Making (MCDM). His areas of research are Decision Making, AHP, ANP, TOPSIS and Forecasting in Management.
MOHAMMAD MODARRES is a Professor at the Sharif University of Technology, Tehran, Iran. He holds masters degrees from Tehran University and The University of California, Los Angeles, and a PhD from The University of California, Los Angeles, Department of Engineering Systems. Mohammed has published widely in operational research and engineering journals, and his research interests include stochastic modelling, revenue management, supply chain management, and mathematical modelling.
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