Download Public Sector OR in Japan: Education, Research, and Applications

ORSI2012, Dec. 20-22
Public Sector OR in Japan:
Education, Research, and Applications
Tatsuo OYAMA
Professor, National Graduate Institute for Policy Studies
7-22-1 Roppongi, Minato-ku, Tokyo 106-8677 JAPAN
Phone : +81-3-6439-6007, Phone & Fax : +81-3-6439-6138
E-mail : [email protected]
Public Sector OR in Japan : Education,
Research, and Applications
• Brief History of ORSJ
• Government officials : Recent trends
• Recruiting and Promoting High-level Government
Official
• Sending Government Officials Abroad
• Educating and Training Government Officials
• Public sector OR in Japan
• Education Activities in Public Sector OR
• Research Activities in Public Sector OR
• Future prospects for OR in public sector
Brief History of ORSJ
• Operations Research Society of Japan (ORSJ)
•
1955 : First meeting was held
•
1956 : First journal Keiei Kagaku
•
(Management Sciences)
•
published
•
1957 : Founding of ORSJ
The Union of Japanese Scientists and Engineers (JUSE), one of the most
representative consulting company in Japan, contributed much for the start
of ORSJ.
“Four years after the foundation of ORSA and TIMS”
Number of memberships were around 350 in 1957, then constantly
increasing, reached 1000 in 1967 and 2000 in 1975. After 1980, however,
total number of memberships has been slightly decreasing.
ORSJ: Trend of Memberships
In 1997 ORSJ had a 40th anniversary conference in Tokyo,
inviting around 10 young researchers from Asian countries to
the APORS (Asia-Pacific Operations Societies) session.
We published a newly revised version of the dictionary of OR
including around 500 applications distributing a CD-ROM to all
society members.
In the following years we published a 40th Anniversary
Series of 15 books called “New Frontier of Management
Sciences”, some of which follow parallel computation in the
mathematical programming, combinatorial optimization－
focusing on the meta heuristics－, queueing algorithm, fuzzy
OR, mathematical modeling in marketing, public policy and
OR, congestion and queue, logistics engineering, production
scheduling and DEA.
In 2007 we held a 50th anniversary conference in Tokyo
again, and also had several memorial events.
Math. Prog./Appl.
Reliability
Queue Th.
Graph Network
Comb. Optimization
Game Th.
Finance
Dynamic Prog.
Scheduling
Statistics
AHP
DEA
Management Sys.
Production Plan.
Simulation
1977－1985 1986－1995 1996－2005 Total(55)
83.1
57.3
36
176.4
66.4
56.8
53
176.2
43.8
67
31
141.8
22.5
49
34.5
106
11.6
38
42
91.6
27
27.5
32
86.5
0
24
45.5
69.5
20
20.5
15
55.5
10.5
23.5
21.2
55.2
32.7
11.3
6.5
50.5
0
10.5
36.5
47
0
9
33.5
42.5
19.8
6.5
13
39.3
5.3
15.5
17
37.8
16.7
14.5
5.5
36.7
1977－1985 1986－1995 1996－2005 Total(55)
Traffics
2.3
12.5
21.3
36.2
Regional
10.8
14.8
7.3
33
Marketing
2
10
20
32
Decision Making
0
23.3
8.5
31.8
Inventory
15.8
6
9.5
31.3
City Plan.
1
0.5
28.8
30.3
Nonlinear Prog.
0
14
12.5
26.5
Forecasting
11
4.8
10
25.8
Total Operation
0
0
23
23
Environments
11.2
7.8
2.8
21.8
Transportation Logistics
0
2.5
17.8
20.3
Markov Process
2.8
9
8.5
20.3
Fuzzy
0
16
3
19
Social System
6.2
10.5
0.5
17.2
Information System
Probability Model
System
OR General
Data Mining
Communication Ntwk
Decision Theory
Maintenance
Search Th.
Integer Prog.
Facility Location
Education OR Literacy
Policy
1977－1985 1986－1995 1996－2005 Total(55)
3.5
3.5
8
15
5.3
7
2.5
14.8
3.5
5
2
10.5
0
9.5
1
10.5
0
1
8.5
9.5
0
0
9
9
5.2
3
0
8.2
4.5
1
2
7.5
2
1.5
4
7.5
1
0
6
7
0
4.5
2.5
7
0
2
4
6
0
2.5
3.5
6
Policy
Modeling
Application
Supply Chain
System Dynamics
PERT
Software
Public System
Renewal
Finance
Linear Prog.
Investment Portfolio
Medical
1977－1985 1986－1995 1996－2005 Total(55)
0
2.5
3.5
6
1
2
3
6
6
0
0
6
0
0
5.5
5.5
2
3.5
0
5.5
3.3
2
0
5.3
0
2
3
5
0.7
1
3
4.7
4.5
0
0
4.5
0
1
3.5
4.5
0
2
2.5
4.5
0.5
4
0
4.5
0
0.5
3.7
4.2
Number of Sessions in Each Area
Period
Math.Prog./Application
Traffic/City Plan.
1977-1985
105.5 (21.81)
18.0 (3.72)
1986-1995
95.3 (14.61)
27.8 (4.26)
1996-2005
70.5 (9.82)
57.5 (8.01)
Total
271.3 (14.63)
103.3 (5.57)
Dynamic Prog./Scheduling
34.8 (7.19)
50.0 (7.67)
54.2 (7.55)
139.0 (7.50)
Reliability
Comb. Optimization
Finance
Management System
AHP
Graph/Network
DEA
Game Theory
Queuing Theory
Public/Policy
Statistics/Simulation
66.4 (13.72)
12.6 (2.60)
0.5 (0.10)
21.8 (4.51)
0.0 (0.00)
22.5 (4.65)
0.0 (1.00)
27.0 (5.58)
43.8 (9.05)
3.2 (0.66)
62.3 (12.88)
56.8 (8.71)
39.0 (5.98)
28.0 (4.29)
17.5 (2.68)
10.5 (1.61)
49.0 (7.51)
9.0 (1.38)
27.5 (4.22)
67.0 (10.27)
13.0 (1.99)
34.2 (5.24)
53.0 (7.38)
49.0 (6.82)
45.5 (6.34)
38.5 (5.36)
36.5 (5.08)
34.5 (4.81)
33.5 (4.67)
32.0 (4.46)
31.0 (4.32)
26.3 (3.66)
23.0 (3.20)
176.2 (7.50)
100.6 (5.43)
74.0 (3.99)
77.8 (4.20)
47.0 (2.54)
106.0 (5.72)
42.5 (2.29)
86.5 (4.67)
141.8 (7.65)
42.5 (2.29)
119.5 (6.45)
Total Operation Project
0.0 (0.00)
2.0 (0.31)
23.0 (3.20)
25.0 (1.35)
Information System
3.5 (0.72)
6.5 (1.00)
18.0 (2.51)
28.0 (1.51)
Transportation Logistic
0.0 (0.00)
2.5 (0.38)
17.8 (2.48)
20.3 (1.09)
Production Planning
0.5 (0.10)
26.2 (4.02)
17.0 (2.37)
43.7 (2.36)
Data Analysis
0.0 (0.00)
3.0 (0.46)
11.5 (1.60)
14.5 (0.78)
Stochastic Process
8.0 (1.65)
12.5 (1.92)
10.5 (1.46)
31.0 (1.67)
11.1 (2.29)
18.5 (2.84)
9.0 (1.25)
38.6 (2.08)
System Modeling
6.5 (1.34)
8.0 (1.23)
8.5 (1.18)
23.0 (1.24)
Education/OR Literacy
0.0 (0.00)
6.0 (0.92)
5.0 (0.70)
11.0 (0.59)
11.2 (2.32)
8.8 (1.35)
4.2 (0.58)
24.2 (1.31)
Social System
6.2 (1.28)
15.0 (2.30)
3.0 (0.42)
24.2 (1.31)
Probability Model
5.3 (1.10)
7.0 (1.07)
2.5 (0.35)
14.8 (0.80)
Case Study
7.0 (1.45)
2.0 (0.31)
2.0 (0.28)
11.0 (0.59)
OR General
6.0 (1.24)
9.5 (1.46)
1.0 (0.14)
16.5 (0.89)
483.7 (100)
652.1 (100)
718.0 (100)
1853.8 (100)
Maintenance/Search
Environments/Resource
Sessions (Total)
Government officials : Recent trends
• Employment examination for government officials
4.36 million government officials
1.114 million (25%) national
3.247 million (75%) local
• Bureaucrats have been losing people’s trust
• “New Public Management” (NPM)
1. Reducing control by the government, and utilizing the
market mechanism
2. Placing value on results rather than plans and processes
• Economic and political impacts of “globalization”
• Governance shift
1. Domestically : from vertical relation to horizontal relation
2. Internationally : from horizontal and independent type to
vertical network type
Recruiting and Promoting High-level
Government Official
Table 1: Numbers of Universities
according to the Type,
passed for Type I Examination
Year
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
National
58
(66.7)
66
(66.0)
66
(64.1)
61
(58.1)
62
(63.9)
68
(65.4)
64
(63.4)
71
(69.6)
61
(61.6)
55
(63.2)
Private
29
(33.3)
34
(34.0)
37
(35.9)
44
(41.9)
35
(36.1)
36
(34.6)
37
(36.6)
31
(30.4)
38
(38.4)
32
(36.8)
Type of
University
() : % to the total
Table 2: Numbers of the applicants,
the passed and the employed
2008
2009
2010
Type Applicants Passed Employed Applicants Passed Employed Applicants Passed Employed
I
II
III
21,200
1,545
605
22,186
1,494
604
26,888
1,314
499
(6,461)
(297)
(154)
(6,903)
(300)
(125)
(8,212)
(272)
(124)
35,546
5,299
2,156
39,940
5,199
2,022
48,040
4,076
-
(11,195)
(1,417)
(549) (12,685)
(1,539)
(566) (14,799)
(1,159)
-
16,119
2,191
1,270
16,417
1,938
984
17,311
1,399
-
(5,308)
(799)
(468)
(5,821)
(736)
(362)
(6,094)
(577)
-
( ) : number of women
The promotion system for Japanese government officials is characterized by
two keywords : “slow” and “prize accumulation”.
Brief History of Sending Government Officials Abroad
• 1862 In the Edo period (1603-1867)
Mr. Griffith’s comment
Young Japanese government officials at that time were all “polite,
sincere, hard-working, earnest and capable” people with the
potential to lead the future Japanese society
Strong will to study and work for themselves and for their own
country
Dr. Heinrich Schliemann
Young Japanese government officials’ sincerity and politeness
• BUSHIDO : The Soul of Japan published in 1899 in the US and written
by a famous Meiji era Japanese scholar and author Dr. and Professor
Inazo Nitobe
Moral standards of Samurai as consisting of such properties as
sacrifice, faithfulness, purity, thrift or plainness, honor, affection and so
on “noblesse oblige”
Samurai were considered and treated as elite with great privilege and
great responsibility
Educating and Training Government Officials
• 16,801 training courses provided and 186,838 government officials
trained. 168 courses and trained 5,915 officials in total by the NPA aimed
at giving necessary knowledge and techniques for them to carry out their
duties and responsibilities.
• More than 1,500 officials to short term courses in the US (1,100), Great
Britain (222), France (116), Germany (50), Canada (34) and Australia (12).
• 970 officials to the United States (481), Great Britain (193), Australia (61),
Germany (48), France (47), Canada (46) and others (94).
• Young government officials tend to quit more frequently
• Authority and responsibility must be established for each position and
government official
• Need to establish our own rule and customs to evaluate each individual’s
contribution to their work more clearly and explicitly
• Need to “invent” an evaluation system
160
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
Figure 3: Total number of government
officials sent abroad
Figure 3.Total Number of Officials sent Abroad
140
120
100
80
60
40
20
0
1000
900
800
700
600
500
400
300
200
100
0
19
65
19
76
19
89
19
91
19
93
19
95
19
97
19
99
20
01
20
03
# of Students
Figure 4 Number of students majored in
policy-related areas
Year
National
Private
Public sector OR in Japan
Public sector segment is described by a huge amount
of statistical data that are obtained by various forms of
processes: surveys, sampling, and other collective
means.
“Reliable” data needs to be used more efficiently and
effectively as we now find the need for various kinds of
policy planning, implementation, and evaluation
becoming more important.
Past contributions of OR, both theoretical and
technical, has not been strong enough in these areas,
even though it has contributed in some degree. Here is
where OR can be applied more actively and positively,
and, thus, we see a bright future for OR in Japan,
especially in the public sectors.
Education Activities in Public Sector OR
Education activities of OR are mainly seen in the
graduate schools having policy-related programs
such as public policy, public administration, public
management, business administration,
development study, urban planning, and so on.
Statistics courses are given in most policy-related
public and private graduate schools in the various
forms of introductory statistics, (intermediate)
statistics, statistical analysis, quantitative data
analysis, statistical methods for policy analysis
introductory mathematics for statistics, and so on.
Technical courses : introduction to simulation,
decision analysis, mathematical modeling for policy
analysis, and theoretical methodology-oriented
courses such as introduction to mathematical
programming, optimization model analysis, (applied
or introductory) game theory discrete optimization
are taught in some graduate programs in GRIPS,
University of Tsukuba and Nanzan University.
Specific statistical courses : categorical data
analysis, experimental designs, multivariate analysis,
and time series analysis are given in University of
Tsukuba Graduate School of Business
Administration and Public Policy.
Research Activities in Public Sector OR
In most policy-related graduate programs
students are required to write master’s thesis
whose research topics are mostly related to their
own interests. In the case that students sent from
their own central and local governments, they tend
to choose their master’s thesis topics close to their
work in their own offices as they are accessible to
the available data.
Recent master’s thesis titles in some graduate
schools are given as follows.
GRIPS
・Applying network model approaches to optimize city waste
collection and transportation systems
・Mathematical modeling analysis on the optimal locationallocation of emergent fire department facilities and staffs
based upon the regional data of the degree of risks
・Mathematical modeling analysis on the connectivity robustness of the disaster prevention communication network
system
University of Tsukuba
・On the relation between voting behavior and regional
characteristics
・Some results for impossibility theorems of social welfare
function and social choice function
・Congestion evaluation system using road user’s recognition
of congestion
T.Oyama,1993; Saitekika moderu bunseki
(Optimization Model Analyses), Nikka Giren
Publishing Co., 372p(in Japanese)
Table of Contents
1. Model Analysis
1.1 System and Mathematical Model
1.2 Data and Model Solution
1.3 Model Manipulation and Sensitivity Analysis
2. Linear Programming Model
2.1 Linear Programming
2.2 Input/Output Model
2.3 Optimal Labor Force Allocation Model
3. Integer Programming Models
3.1 Integer Programming
3.2 Train Scheduling Model
3.3 Power Utilities Construction Planning Model
4. Graph Optimization Model
4.1 Graph Theory
4.2 Maritime Salvage Boats Location Model
4.3 Public Facilities Location Model
5. Network Optimization Models
5.1 Network Theory
5.2 Energy Network Model
5.3 Road Traffic Network Model
6. Queueing Combined Integer Programming Models
6.1 Queueing Theory
6.2 Optimization Model for Information System
7. Markov Models
7.1 Markov Process
7.2 Industrial Structure Model
7.3 Labor Force Transition Model
8. Gravity Models
8.1 Law of Gravity and Gravity Model
8.2 Commodity Flow Model and Information
Service Flow Model
8.3 Population Move Model
9. Entropy Models
9.1 Entropy and Entropy Model
9.2 Commodity and Information Flow Model
9.3 Interregional Telephone Calls Flow Model
T.Oyama and T.Sueyoshi,2002;
Public Policy and OR,
Asakura Shoten Publishing Co.,271p(in Japanese)
Ⅰ Basic Theory for Mathematical Model Analysis
1. Public Policy and Mathematical Model Analysis
1.1 Mathematical Model and Data
1.2 Mathematical Model Analysis
2. Basic Mathematical Model
2.1 One-variable Mathematical Model
2.2 Continuous-type Stochastic Model
2.3 Discrete-type Stochastic Model
3. Forecasting and Evaluation
3.1 Forecasting Methods
3.2 Regression Analysis
3.3 DEA
4. Optimization and Simulation
4.1 Continuous-type Optimization Model
4.2 Discrete-type Optimization
4.3 Simulation
5. Stochastic Phenomena and Game
5.1 Markov Model
5.2 Queueing Simulation
5.3 Game Theory
Ⅱ Application of Mathematical Model to Public Sectors
6. Application to Traffics and Transportaion
6.1 City Traffics Data Analysis
6.2 Mathematical Model Analysis for Planning City Bus
Routes
6.3 P&R Panning via Shortest Path Counting Method
7. Application to Quantitative Evaluation Problems
7.1 Regression Analysis for Measuring Salary Gaps
7.2 DEA Model Analysis for Measuring Efficiency of Electricity
Generation Sectors
8. Application to Public Facility Location Problems
8.1 Optimal Facility Location Model Analysis for the Health and
Welfare Services for the Aged
8.2 Mathematical Model Analysis for the Optimal Location of Post
Offices
8.3 Optimal Location Mathematical Model Analysis of P&R Facilities
9. Application to Energy Policy and Public Utilities
9.1 Markov Model Analysis for the Electricity Supply and Demand
9.2 Mathematical Model Analysis for the Optimal Electricity Supply
System
9.3 Optimization Model Analysis for Introducing Diversified
Electricity Resource MGT
T. Oyama(ed.), 1998;Handbook of Public Policy
OR(Translation from Operations Reserch and the
Poblic Sector, Elsevier Science),Asakura Shoten
Publishing Co.,776p(in Japanese)
[1] H. Takasakura and T. Oyama, 1994; “Optimization of collection and
transportation system of city wastes”, Communications of Operations Research,
Operations Research Society of Japan, Vol.39, No.12, pp.653-658 (in Japanese).
[2] T. Oyama and T. Ichimori, 1995. "On the Unbiasedness of the Parametric
Divisor Method for the Apportionment Problem", Journal of Operations Research
Society of Japan, Vol.38, No.3, pp.301-321.
[3] M. Hata T. Oyama, 1995. "Application of hierarchical mathematical
programming model for the optimal facility location problem of the aged",
Proceedings of the RAMP Symposium ‘95, Mathematical Programming Research
Group, Operations Research Society of Japan, pp.91-106 (in Japanese).
[4] T. Oyama, 1996. "Optimizing city waste collection and transportation systems
via the application of network model approaches", Perspectives of Advanced
Technology Society 3 : Urban Life and Traffic, Y. Matsuda and M. Fushimi (eds.),
Maruzen Planet Co., Tokyo, Japan, pp.21-36.
[5] M. Miwa, T. Ishikawa and T. Oyama, 1998: “Basic investigation on building the
transition process model of railway track irregularity”, Proceedings of J-RAIL’98,
Federation of Railway Technology, pp.443-446 (in Japanese).
[6] T. Oyama, 1999; “Mathematical model analyses on the optimal location of
advanced medical instruments MRI”, Chap. 3, Research Report on evaluating
advanced medical instruments MRI, Medical Economy Research Association, Vol.7,
pp.47-66 (in Japanese).
[7] T. Oyama, 1999; “Regional inequality analyses and mathematical model
analyses for the location of advanced medical instruments MRI”, Communications
of Operations Research, Operations Research Society of Japan, Vol.44, No.7,
pp.361-364 (in Japanese).
[8] T. Oyama, H. Tamura, and T. Sano, 1999; “Research on the location of post
office facilities”, Monthly Research Report of Post and Telecommunications”,
Research Institute of Post and Telecommunications, No.11, pp.4-23 (in Japanese).
[9] M. Miwa, T. Ishikawa and T. Oyama, 1999: “Building the transition process
model and its application to the MTT operation planning”, Proceedings of JRAIL’99, Federation of Railway Technology, pp.443-446 (in Japanese).
[10] Miwa, M., T. Ishikawa and T. Oyama, 1999: "Modeling the transition process
of railway track irregurarity and its application to decision making for
maintenance strategy", Proceedings of WCRR'99, Tokyo, 4p.
[11] T. Oyama, N. G. Hall and K. Kobayashi, 2000: “Generalizing divisor method for
the apportionment problem --- theoretical development and numerical
experiments”, Optimization : Modelling and Algorithm 13, Mathematical Statistics
Research Institute, pp. 47-73.
[12] Nagano, S. and T. Oyama, 2000 : "Mathematical programming model
analyses on minimizing regional gap of health care services and finding an optimal
facility location for the elderly", Communications of Operations Research,
Operations Research Society of Japan, Vol.45, No.12, pp.33-41 (in Japanese).
[13] Mizuno, K. and T. Oyama, 2001 : "Mixed integer programming model analyses
for the optimal electricity supply system in the post-liberalization period",
Communications of Operations Research, Operations Research Society of Japan,
Vol.46, No.9, pp.33-41 (in Japanese).
[14] Miwa, M., T. Ishikawa and T. Oyama, 2001: "Modeling the transition process
of railway track irregurarity and all-integer type mathematical programming
model analyses for the optimal planning of the track maintenance schedule",
Journal of Civil Engineering Society, No.681/IV-52, pp.51-65.
[15] Ojima, J. and T. Oyama, 2003 : “Index gap minimization model analyses for
local promotion branches of Iwate Prefecture”, Communications of Operations
Research, Operations Research Society of Japan, Vol.48, No.8, pp.567-573 (in
Japanese).
Future prospects for OR in public sector
Policy evaluation has become more necessary, important, and also very
common with the emerging attention to the new public management.
(so-called NPM) Also, much quantitative data has been gathered and
prepared by all Japanese governmental organizations.
Note that OR theory and techniques that take advantage of this data
have not been applied effectively so far (this is also the case for public
sector research in other countries).
There are also many policy issues and problems that have not been
considered seriously by OR researchers, even though their solutions are
important and needed in the near future.
These global problems arise in the areas of environment, energy
resources, complex societal problems such as recycling, information
technology industries, natural disasters and other emergent risk
situations; they all require appropriate policy decision making. They are
worthy challenges to OR researchers.
Thank you very much