Queuing search algorithm: A novel metaheuristic algorithm for solving engineering optimization problems

• Published in: Applied Mathematical Modelling Vol. 63; pp. 464 - 490
• Main Authors: Zhang, Jinhao, Xiao, Mi, Gao, Liang, Pan, Quanke
• Format: Journal Article
• Language: English
• Published: New York Elsevier Inc 01.11.2018; Elsevier BV
• Subjects: Algorithms; Customer services; Engineering; Engineering optimization; Heuristic methods; Metaheuristic algorithms; Optimization; Queues; Queuing; Queuing search algorithm; Search algorithms; Queuing search algorithm; Engineering optimization; Metaheuristic algorithms
• ISSN: 0307-904X; 1088-8691; 0307-904X
• DOI: 10.1016/j.apm.2018.06.036

•A novel metaheuristic algorithm called queuing search (QS) is proposed, which is inspired from human activities in queuing process.•QS does not need to preset the other parameters except the population size and stopping criterion.•Performance of QS is checked for thirty bound-constrained benchmark functions and some constrained engineering optimization problems.•QS shows the great ability of jumping out of a local optimal solution and searching the global optimum. This paper presents a novel metaheuristic algorithm called queuing search (QS), which is inspired from human activities in queuing. Some common phenomena are considered in QS: (1) customers actively follow the queue that provides fast service; (2) each customer service is mainly affected by the staff or customer itself; and (3) a customer can be influenced by others during the service when the queue order is not strictly maintained. The performance of QS is tested on 30 bound-constrained benchmark functions scalable with 30 and 100 dimensions from CEC 2014, 5 standard and 4 challenging constrained engineering optimization problems. Meanwhile, comparisons are performed among the results of QS and some state-of-the-art or well-known metaheuristic algorithms.