The development of a large theme park usually includes multiple phases. The combination and development ordering of facilities in these phases have a great impact on the attractiveness of the theme park. Examples of such facilities are attractions, food service, accommodation, and supporting facilities. Some of these facilities although highly profitable, cannot attract visitors on their own, while others may boost the visitor count, yet by themselves do not make a profit. This research considers the values that each development activity brings to the project, and prioritizes feasible alternatives based on their net present values. Based on the integration of simulation and the genetic algorithm, a decision support system has been developed to determine the combination and ordering of facilities, and the resources needed for each development step. This development plan will provide investors with systematic and quantitative information that will help them to determine the development portfolio of each facility under the constraint of the funding program.
Developing a theme park may often span decades,
requiring a high level of capital investment, and a large parcel
of land to build a large number of facilities on. Consequently,
the project scheduling is usually contracted out to
a consulting firm, and includes: (1) a project feasibility
study and an estimate of the development scale; (2) the initial
design concept of the facilities; (3) a stage-based development
progress and a financial model; and (4) a list of the
detailed designs of facilities that need to be developed.
Inappropriate strategy as well as incorrect scheduling
may cause the failure of any development project, and
especially that of a theme park. Disneyland Resort Paris
is a case in point. Within eighteen months after its opening,
it had lost 10 billion US dollars. Up to December 1993, less
than two years after the opening, not only was the initial
capital consumed, but they had to raise an additional loan
of 1.75 billion US dollars to maintain the operation (Spencer,
1995). Three months later, a new crisis threatened its
survival. Two major oversights attributed to the failure
of this development project. First, Paris is located at about
48 latitude, and relatively close to the North Atlantic
Ocean, resulting in cold and wet winters. This fact alone
will drastically decrease the enthusiasm of people to participation
in the outdoor activities offered by the theme park.
However, this fact was simply neglected. Second, even
though the visitor count was expected to decrease in the
cold wintry months, excessive shows and activities kept
being launched, resulting in an even further waste of
capital. An additional issue that was not considered or
investigated was the fact that there is a fair amount of
‘‘anti-Americanism’’ in France, and Disney is seen as the
epiphany of US commercialism by many French as well
as many Europeans.
The case of Disneyland Resort Paris shows the vital
importance of having the right strategy and a correct schedule
prior to even executing such large a project. During
the extensive period of project development, continuously
changing risks become embedded in the construction costaffecting the operation of each facility, as well as the relationship
between facilities, especially those involving the
supply of resources. The fact that the planner will have
to consider multiple variable factors simultaneously is inevitable.
This will make it very difficult to settle on an optimal
development strategy among the multitude of combinations
of potential facilities and scheduling plans. Therefore,
support in the decision making process of the development
schedule will aid the planner to better understand the influence
of each variant on the project outcome, as well as the
effectiveness of each schedule combinations, allowing him
to determine the optimal development strategy.
Various researches have focused on the issue of modeling
the project decision-making and plan optimization,
such as the Multi-Criteria Decision Model (e.g., Hsieh &
Liu, 1997), Resource-Constrained Scheduling (e.g., Leu &
Hwang, 2002), and the Ranking and Combination of the
Project Investment Model (e.g., Ghasemzadeh & Archer,
2000). These models are unsuitable for theme park development
projects because they cannot simultaneously deal
with selection, ordering, and scheduling of feasible investment
items.
For example, Hsieh and Liu’s Time-series Combinatorial
Planning Model in Infrastructure Plan (Hsieh & Liu,
1997) has two assumptions: (1) sub-projects are independent
to each other, and (2) activities cannot be separated
or partially completed. These two assumptions are unsatisfactory
for a theme park development. Example 2, Most
Resource-Constrained Scheduling models fail to consider
the selection of activities (i.e., not every activity must be
executed) but can only provide solutions with specified
activities and resources. Example 3, Ghasemzadeh and
Archer’s supporting system for decision making of a portfolio
with multiple items (Ghasemzadeh & Archer, 2000)
fails to consider potential situations when the start and finish
dates of items are movable.
This study is aimed at constructing a decision support
system for the decision-making process when laying out
the order of a development plan. The project planner
inputs the activities, their start and finish dates, estimated
costs and revenues, and resource relationships. All these
data are simulated and analyzed in order to predict the
overall effectiveness of the project. Various schedule combinations
will be calculated to determine the best development
strategy so as to provide the planner with a point
of reference. This will help overcome the complexities of
the decision-making in the development of a theme park
facility. This study attempts to achieve its goal through
the following approaches:
(1) Investigate the characteristics of a theme park development
project, the different types of facilities and
their features, characteristics of different types of
strategies and scheduling systems, and the demand,
supply, and the effect of different facilities.
(2) Construct a simulation network model of a theme
park development project, that includes all the
features and correlations of the activities involved
in the planning, construction, and operation.
(3) Integrate the polyploidy genetic algorithm (GA) and
the simulation analysis to design a decision support
system for determining the project strategy and schedule
plan with the maximum net present value (NPV)
for the reference of project investors and planners.
construction projects and optimization of financial portfolio.
However, very few studies have been dedicated to the
problem of theme park development, which requires consideration
of both scheduling and portfolio optimization.
This study analyzed the features of theme park development
projects and divided the associated facilities into five
categories.
To facilitate the scheduler to develop the optimal project
schedule, the proposed AVO-PLAN system integrates simulation
and the GA to predict the NPV of each combination
and determine the priorities of each facility with the
GA. The priority values of each facility in each time unit
are expressed with genetic coding, and the optimal development
strategy and scheduling are determined after generations
of evolutions.
Since the focus of a theme park development project is
the value of the investment items, and since there is a complicated
demand-and-supply relationship between activities,
the genetic coding with start and finish date of each
activity may not reflect the importance of execution for
each item. Unlike other studies of scheduling with the aid
of the GA, AVO-PLAN incorporates the priority values
of each development item in each time unit into genetic
coding, so as to facilitate a quicker search of near-optimal
solution via simulation. In addition, this study also combined
the priority values of each time unit into a polyploidy
genetic structure, which provides a better reflection of the
Time-series than ordinary applications with haploid.
The testing in our case study revealed that AVO-PLAN
surpassed the experts by a faster search and a better NPV.
With regards to the demand-and-supply relationship of the
resources between activities; the experts couldnot provide a
thorough consideration in their scheduling, while AVOPLAN
integrates it completely into the project scheduling
via simulation. Scheduling of theme park requires a considerable
versatility of combination. In the past, its completion
relied on the experience of experts. On the other
hand, AVO-PLAN applies the GA to effectively figure
out the near-optimal project scheduling for schedulers.
Our proposed system can not only be applied to theme
park development projects but also to the decision-making
and scheduling portions of other projects that require
staged or segmented execution, such as staged urban
renewal projects.