本文主要介紹兩個熵基礎式的交通量指派中的路徑選擇模型。第一個模型為極大熵用路人均衡模型（Maximum entropy user-equilibrium，MEUE）。第二個模型為熵基礎式的交通量分配模型（Entropy-based traffic assignment，EBTA）。這兩個模型是Chen的雙目標一般化熵基礎式的交通量分配模型的特殊例子（Chen，2015a）。這兩個模型都體現路徑集合唯一性及比例原則的特點。並且，兩個交通量指派模型都具有路徑唯一解的特性。對於求解MEUE模型我們探討了TAPAS演算法（Bar-Gera,2010）以及提出了一種新的變異演算法，並比較了兩者間的運算效率及數值結果。進而，我們發展了一種新的PAS基礎式的演算法求解EBTA模型並驗證了其收斂性及數值結果。;In this thesis, we focus on two entropy-based route choice models of traffic assignment, namely maximum entropy user-equilibrium (MEUE) and entropy-based traffic assignment (EBTA). These two problems are two special cases of Chen’s two-objective model formulation for the entropy-based traffic assignment (Chen, 2015a). And the properties of route set consistency and proportionality are assumed and be contained in these two problems which are regarded as the condition of unique route flow solution as well. Therefore, the solution algorithm for the MEUE named TAPAS (Bar-Gera, 2010) would be discussed exhaustively and a mixed variant algorithm are also provided for comparing. Furthermore, we propose a new primal PAS-based algorithm called meta-TAPAS for solving the EBTA problem. The performance of such new algorithm is also detailed discussed and examined.
