## 6 Conclusions and Future Works  
This study addresses the integration and composition optimization challenges of industrial software systems operating in heterogeneous environments. To tackle issues such as insufficient reliability and difficulty in balancing QoS during service selection, a bi-objective optimization model is proposed. The model comprehensively considers service time, cost, reputation, delivery quality, and availability. Service availability is quantified using MTBF and MTTR, while service dependencies and integration uncertainties are incorporated to construct a service optimization framework suitable for multi-source heterogeneous systems. Building on this model, a set of coordinated strategies--namely chaotic initialization, differential evolution, and Levy flight mechanisms--is introduced to enhance the quality, stability, and convergence efficiency of multi-objective optimization in industrial software service composition. Based on these strategies, the HEMOGWO algorithm is developed. It integrates Tent chaotic mapping to improve population diversity, incorporates an improved differential evolution operator to enhance local precision, and applies a Levy flight-based mechanism to strengthen global search capability. To verify the effectiveness of the proposed method, a dual experimental framework was designed, incorporating both standard benchmark functions and real-world industrial tasks. The performance of HEMOGWO was compared against several mainstream multi-objective algorithms, including NSGA-III, MOPSO, MOEAD_DE, MOGWO, and its improved variant, SMOGWO. The results show that HEMOGWO achieved the best performance in terms of GD and IGD metrics on most benchmark functions. For nine types of SCOS-based real-world composition optimization tasks, HEMOGWO also obtained the lowest mean GD and IGD values across the majority of test scales. Its superiority was further confirmed through the Wilcoxon signed-rank test, particularly in terms of improved solution accuracy and computational speed compared with SMOGWO. The main contributions of this study are as follows: (1) a bi-objective SCOS model integrating QoS and availability is proposed, introducing system-level availability modeling into industrial software service composition optimization for the first time; (2) a HEMOGWO algorithm incorporating multiple intelligent search mechanisms is developed, and its performance advantages are validated; and (3) a combined testing framework based on standard benchmark functions and industrial scenarios is designed to comprehensively evaluate the algorithm's generalization ability and practical applicability. Certainly, this study has several limitations. First, the experimental dataset is primarily constructed based on real-world parameter distributions but does not capture dynamic behavioral dependencies or real-time interaction logic among services. Second, the service composition process is modeled statically, without accounting for practical constraints such as multi-user requests, service fluctuations, and resource contention. Moreover, the balance between real-time performance and computational complexity in the proposed algorithm requires further optimization. Future research can address these issues in several ways--by introducing log-driven dynamic workflow modeling to enhance the realism of test data; by extending HEMOGWO to dynamic environments and multi-tenant service scheduling tasks; and by exploring its online deployment capability and engineering implementation within industrial cloud platforms. These efforts aim to promote the algorithm's broader application in intelligent manufacturing scenarios. Conceptualization, S.L. ; methodology, Y.C. and S.L. ; software, Y.C. ; validation, C.L. and H.Y. ; formal analysis, Y.C. ; investigation, Y.C., H.Y. and Y.W. ; resources, S.L. and C.L. ; data curation, Y.C., H.Y. and Y.W. ; writing--original draft preparation, Y.C. ; writing--review and editing, Y.C. and S.L. ; visualization, Y.C. and C.L. ; supervision, S.L. ; project administration, S.L.