Analyzing throughput is very important for the design, optimization, and management of production lines. In this paper, we present an efficient throughput analysis approach for production lines with merging, splitting, and recirculating topologies. In particular, we define a decomposition regulation based on queue modules for the decomposition of the various topologies, and we improve an iterative approximation method for calculating and iterating the queue module state probabilities until the throughput of the production line is obtained. To decrease the computation time and automate the calculation process of the queue module state probabilities, we build a queue module database that includes the solution equations of common queue module state probabilities. The numerical examples show that our approach calculates the throughput of production lines with merging, splitting, and recirculating topologies with high accuracy (≥90%) and efficiency (completed in ten min). Our contribution is an efficient throughput evaluation methodology that can be used to rapidly estimate the performance and the cost of production lines with various topologies in the conceptual design phase of production lines in the industry. INDEX TERMS Approximation method, production engineering, queueing analysis, topology, throughput. The associate editor coordinating the review of this manuscript and approving it for publication was Huaqing Li. FIGURE 1. Recirculating production line that includes merging, splitting, and recirculating topologies simultaneously.

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This study addresses the challenging problem of efficient buffer allocation in production lines. Suitable locations for buffer allocation are determined to satisfy the desired throughput, while a suitable balance between solution quality and computation time is achieved. A throughput calculation approach that yields the state probability of production lines is adopted to evaluate the effectiveness of candidate buffer allocation solutions. To generate candidate buffer allocation solutions, an active probability index based on state probability is proposed to rapidly detect suitable locations of buffer allocations. A variable neighborhood search algorithm is used to maintain acceptable solution quality; an additional neighborhood structure is used in the case where no satisfactory solution is generated in the initial neighborhood structure. Extensive numerical experiments demonstrate the efficacy of the proposed approach. The proposed approach can facilitate agile design of production lines in industry by rapidly estimating production line topologies.

The multi-objective buffer allocation problem of production lines is a non-deterministic-polynomial-hard problem. Many metaheuristic algorithms have been proposed to solve this problem. However, further investigation of new algorithms is still required because metaheuristic algorithms highly depend on the problem types. Furthermore, the balance between the solution quality and computational efficiency requires further improvement. Therefore, a data-driven algorithm consisting of the black widow optimizer and simulated annealing algorithm is proposed to maximize throughput and minimize energy consumption in production lines. Numerical examples demonstrate that the proposed algorithm achieves better solution quality than other state-of-the-art algorithms without losing computational efficiency. This study contributes to multi-objective optimization of resource scheduling in production lines.