Abstract:
Developing a comprehensive service strategy to optimize customer satisfaction presents an ongoing challenge for effective facility provider. The essence of comprehensive systems is selecting the suitable service design, establishing an effective service delivery process, and building continuous improvement. This research analyzes a finite capacity service system incorporating several realistic customer-server dynamics: customer impatience, server’s partial breakdown, and threshold recovery policy. When the number of customers is more, the server is under pressure to increase the service rate to mitigate the service system’s load. Motivating from this fact, the concept of service pressure condition is also incorporated. For characterization, we evaluate state probabilities derived using the matrix-analytic method and henceforth several performance measures. To address the cost optimization problem involving the developed Chapman-Kolmogorov forward differential-difference equations and determine optimal operational parameters, we employ the recently devised cuckoo search (CS) optimization approach. A comparative analysis is performed with the semi-classical optimizer: quasi-Newton (QN) method, and metaheuristics technique: particle swarm optimization (PSO), to validate the efficacy of results. Lastly, several numerical illustrations are depicted in different tables and graphs to understand essential characteristics quickly.