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Multiobjective routing in a Metropolitan City with deterministic and dynamic travel and waiting times, and one-way traffic regulation
Published in CRC Press
2017
Pages: 211 - 242
Abstract
The shortest path problem is the problem of finding one-to-one path from the source to the destination. In real life, the problem involves conflicting and competing objectives, and many researchers solve the multiobjective shortest path optimization problem using a weighted linear combination of objectives. However, the solution of weighted sum is highly sensitive to the weights given, limiting the practicability of this method. Solving the problem by simultaneous optimization of the objective functions to generate a set of nondominated solutions can help to build a decision support system for travelers to choose their own path on the basis of their individual preferences. This chapter proposes a multiobjective mathematical model, solved using e-approach to obtain (heuristically) nondominated solutions of shortest paths with respect to time and distance. In this study, we consider minimizing both distance and time as the objective functions with real-life constraints such as time-dependent dynamic and deterministic travel times, time-dependent dynamic and deterministic waiting times, and time-dependent one-way traffic along the roads. We implement the proposed model by using the real-life planning data (1658 nodes and 4224 links) of Chennai city network (a metropolitan city in India with highly interconnected network of roads), and present the discussion on the multiobjective routing problem with real-life considerations. © 2017 by Taylor & Francis Group, LLC.
About the journal
JournalBig Data Analytics Using Multiple Criteria Decision-Making Models
PublisherCRC Press
Open AccessNo
Concepts (14)
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    Decision support systems
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    Graph theory
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    Optimization
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    Street traffic control
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    Travel time
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    INDIVIDUAL PREFERENCE
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    INTERCONNECTED NETWORK
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    MULTIOBJECTIVE MATHEMATICAL MODEL
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    MULTIOBJECTIVE ROUTING PROBLEMS
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    Nondominated solutions
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    Simultaneous optimization
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    TIME-DEPENDENT DYNAMICS
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    WEIGHTED LINEAR COMBINATIONS
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    Problem solving