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The integration of the metro and bus operation planning is a
fuzzy multiobjective optimization problem. The traditional de-
cision theory ignores the problems of imprecision and of fuzzi-
ness,so it is often criticized in practical cases.
Transportation specialists do not pay enough attention to this
issue, either. The purpose of this paper is to solve the fuzzy
optimization problem of the operation plan under a fixed and
variable demand. To determine a suitable compromize solution,
this study will use the concept of maximizing the smallest
normalized diviation from aspiration levels to develop an
algorithm. In empirical study, it has been found that the
weighted operator, not the min operator, is suitable for the
fixed demand model. To evaluate the alternatives of this
operation plan, this study develops evaluation models
according to the individual de- cision and the group decision.
In the individual decision model, this study uses fuzzy
synthetic decision, approximation reasoning and fuzzy
linguistic approach to develop a multiple-layered de- cision(
MLD) model. This MLD model can solve the problem of trans-
ferring a basic level model to a higer level one. In the group
decision model, this study uses fuzzy measure theory to revise
the AHP model. According to the case study, the fuzzy measure
AHP can provide more information for decision makers. This
model can solve some problems that traditional AHP can not
deal with, like decision attribute dependence, average value,
fuzziness number and consensus decision problems. Because the
fuzzy AHP can deal with decision attribute dependence problem,
this study puts the evaluator at the decision making process to
develop a con- sensus decision model. From the case study, the
opinion of the minority will not be ignored, so this model is
very suitable for the studies in conflicting decision
environments.
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