###### Abstract  
In a human-robot collaborative disassembly line, multiple people and robots collaboratively perform disassembly operations at each workstation. Due to dynamic factors, such as end-of-life product quality and human capabilities, the line balancing problem for the human-robot collaborative disassembly line is a dynamic optimisation problem. Therefore, this paper investigates this problem in detail and commits to finding the evolutionary dynamic optimisation. First, a task-based dynamic disassembly process model is proposed. The model can characterise all feasible task sequences of disassembly operations and the dynamic characteristics of tasks affected by uncertain product quality and human capabilities. Second, a multiobjective optimisation model and a feature-based transfer learning-assisted evolutionary dynamic optimisation algorithm for the dynamic human-robot collaborative disassembly line balancing problem are developed. Third, the proposed algorithm uses the balanced distribution adaptation method to transfer the knowledge of the optimal solutions between related problems in time series to track and respond to changes in the dynamic disassembly environment. Then, it obtains the optimal solution sets in a time-varying environment in time. Finally, based on a set of problem instances generated in this study, the proposed algorithm and several competitors are compared and analysed in terms of performance indicators, such as the mean inverted generational distance and the mean hypervolume, verifying the effectiveness of the proposed algorithm on dynamic human-robot collaborative disassembly line balancing. dynamic disassembly line balancing; human-robot collaboration; disassembly process model; evolutionary dynamic optimisation; transfer learning +
Footnote †: journal:  
Since the 1990s, robot-based disassembly systems have received extensive attention from the academic community, and researchers have carried out much work on automated disassembly cells. However, these works are mainly oriented to the structured environment, and they cannot deal with various uncertainties, which significantly limits their industrial applications. With the development of information technologies, such as ubiquitous perception, industrial robots, and artificial intelligence, autonomous disassembly systems that can effectively tackle environmental uncertainties have gradually attracted attention and made progress [2]. In disassembly systems, a disassembly line composed of multiple workstations connected in sequence through a transmission module is an operation mode that is suitable for remanufacturing enterprises to implement product disassembly. Compared to the disassembly cell, it can guarantee higher productivity. Building the autonomous disassembly system represented by the robotic disassembly line is a long-term goal of disassembly research. Robots have significant advantages over humans in strength, speed, repeatability, and stamina. However, due to the low flexibility of robots and their limited cognitive capabilities, some complex and sophisticated tasks still require humans to complete them [3]. Moreover, the dynamic structure of the robot is complex [4], and no robot can handle all possible tasks. Human-robot collaboration can effectively utilise the complementary advantages between robots and humans, and it will be an important mode for product disassembly. Therefore, constructing a human-robot collaborative disassembly line (HRDL) that can deal with various environmental uncertainties should be a feasible direction in the present and future disassembly fields. The disassembly line balancing problem (DLBP) is a crucial planning problem in the disassembly line. It considers how to allocate a set of disassembly operations to the operators in the workstations to ensure that the constraints are not violated, while also optimising various predetermined performance measures [5]. In the HRDL, multiple humans and robots collaboratively perform operations at a workstation.