Title of article :
Composite goal methods for transportation network optimization
Author/Authors :
Veluscek، نويسنده , , Marco and Kalganova، نويسنده , , Tatiana and Broomhead، نويسنده , , Peter and Grichnik، نويسنده , , Anthony، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2015
Pages :
16
From page :
3852
To page :
3867
Abstract :
Lately the topic of multi-objective transportation network optimization has received increased attention in the research literature. The use of multi-objective transportation network optimization has led to a more accurate and realistic solution in comparison to scenarios where only a single objective is considered. The aim of this work is to identify the most promising multi-objective optimization technique for use in solving real-world transportation network optimization problems. We start by reviewing the state of the art in multi-objective optimization and identify four generic strategies, which are referred to as goal synthesis, superposition, incremental solving and exploration. We then implement and test seven instances of these four strategies. From the literature, the preferred approach lies in the combination of goals into a single optimization model (a.k.a. goal synthesis). Despite its popularity as a multi-objective optimization method and in the context of our problem domain, the experimental results achieved by this method resulted in poor quality solutions when compared to the other strategies. This was particularly noticeable in the case of the superposition method which significantly outperformed goal synthesis.
Keywords :
Multi-goal methods , Logistics optimization , Ant Colony Optimization , Transportation network optimization
Journal title :
Expert Systems with Applications
Serial Year :
2015
Journal title :
Expert Systems with Applications
Record number :
2355859
Link To Document :
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