Markovian queue optimisation analysis with an unreliable server subject to working breakdowns and impatient customers

• Published in: International journal of systems science Vol. 46; no. 12; pp. 2165 - 2182
• Main Author: Liou, Cheng-Dar
• Format: Journal Article
• Language: English
• Published: Taylor & Francis 10.09.2015
• Subjects: Customers; Decision making; epsilon-constraint method; impatient customers; Markov processes; Mathematical models; Optimization; Pareto front; Pareto optimality; particle swarm optimisation; Queues; Service stations; working breakdown
• ISSN: 0020-7721; 1464-5319
• DOI: 10.1080/00207721.2013.859326

This study investigates an infinite capacity Markovian queue with a single unreliable service station, in which the customers may balk (do not enter) and renege (leave the queue after entering). The unreliable service station can be working breakdowns even if no customers are in the system. The matrix-analytic method is used to compute the steady-state probabilities for the number of customers, rate matrix and stability condition in the system. The single-objective model for cost and bi-objective model for cost and expected waiting time are derived in the system to fit in with practical applications. The particle swarm optimisation algorithm is implemented to find the optimal combinations of parameters in the pursuit of minimum cost. Two different approaches are used to identify the Pareto optimal set and compared: the epsilon-constraint method and non-dominate sorting genetic algorithm. Compared results allow using the traditional optimisation approach epsilon-constraint method, which is computationally faster and permits a direct sensitivity analysis of the solution under constraint or parameter perturbation. The Pareto front and non-dominated solutions set are obtained and illustrated. The decision makers can use these to improve their decision-making quality.