Within the paper, we study several variants of the decision problem, Scheduling with precedence constraints and time windows, denoted by \(P \mid prec,r_i,d_i \mid \star \) , and present improved fixed-parameter algorithms parameterized by the maximum processing time \(p_{\max }\) and the maximum number \(\mu \) of overlapping time windows, defined as \(\mu =\max _{t \in \mathbb {N}}|\{ i \in S \mid r_i \le t < d_i \}|\) . Firstly, we propose an algorithm for \(P \mid prec,r_i,d_i \mid \star \) with time complexity \(O((p_{\max }+2)^{\mu }p_{\max }n^3)\) , where n is the number of tasks. This significantly improves the previously best-known algorithm with time complexity \(O(p_{\max }^{2\mu } \cdot 16^{\mu }\sqrt{\mu } \cdot n^3)\) . Then for the unit processing time case \(P \mid prec, p_i = 1, r_i,d_i \mid \star \) , we further develop an algorithm with time complexity \(O(2^{\mu }\mu mn^3)\) , where m is the number of machines, improving the previously best-known algorithm with time complexity \(O(16^{\mu }n^4)\) . Finally, we extend the two algorithms to the typed machine setting, solving \(P \mid \mathcal {M}_j(type),prec,r_i,d_i \mid \star \) and \(P \mid \mathcal {M}_j(type),prec,p_i=1,r_i,d_i \mid \star \) , with time complexities \(O((p_{\max }+2)^{\mu } p_{\max } n^3)\) and \(O(2^{\mu }\mu m^kn^3)\) , respectively, where k is the number of machine types.