## 2 A Division of Manual Labor, Assembly and Production Lines
### Changing Customer Demand and Optimization of Operation Sequences  
The assembly sequence and path planning problem involves finding a proper sequence of parts to be assembled into a finished product and to shorten assembly paths for each such part. This problem combines assembly sequence planning and assembly path planning, which are both NP-hard problems and are therefore intractable for a large problem size. In most published results on this problem, it was assumed that path planning was monotone (i.e., each part was moved only once) and each part was completely rigid. Such simplifications are limiting assumptions. Indeed, most assembled complex products such as ships, aircraft and automobiles are composed of rigid and flexible parts. The required generation of an assembly sequence and a path plan for most real-world complex products requires an intermediate placement of parts to be taken into account. The article [61] presents an algorithm for solving both monotone and non-monotone problems for rigid and flexible parts. This algorithm uses an assembly matrix for describing different relations between all pairs of parts and the amounts of compressive stresses needed for assembling flexible parts and obtains a tentative assembly sequence using a greedy algorithm. Short assembly paths are iteratively computed from the initial one to the goal configurations of the parts using a sample path planner. In case of a failure, if the part is flexible, it is determined whether the part can still be assembled by undergoing deformation. To evaluate the developed algorithm, two products were designed, and the problem was solved via four combinations of the proposed algorithms. The means and standard deviations of five criteria were calculated. The computational results showed that the greedy heuristic algorithm outperformed other algorithms with at most a 4.6% average gap in path length and a 2.1% average gap in the CPU time compared to the best solution. The diversification of customer demand poses a great challenge for many manufacturing enterprises and the scheduling problems of material handling affects the efficiency of assembly conveyers. In the article [62], a scheduling algorithm and a static kitting strategy were proposed in order to solve scheduling problems of the material handling for automotive mixed-model assembly lines based on the integrated super-markets. An integer programming was established with the objective to minimize the number of logistic workers. An improved kitting strategy was presented to solve the problem heuristically and a model based on the graph theory was constructed to transform the considered scheduling problem to another known one. The algorithm was developed to solve the scheduling problem. Computational experiments for the proposed algorithms were carried out in order to compare the proposed algorithms with published ones. The feasibility and effectiveness of the proposed algorithms were verified by the obtained computational results. In the article [63], an assembly plan was investigated as one of the assembly stages to minimize the cost of a manufacturer and to ensure the safety of an assembly part. The problem of assembly sequence planning is how to reduce the deviation from the real manufacturing conditions. The authors of this paper have investigated an approach to automatically generate the assembly sequences for the industrial field. A physically based assembly representation model includes the predetermined basic assembly information (precedence relations between parts or subassemblies, geometric constraints, different assembly types) and the dynamic real-time properties (the center position of gravity, the force strength of the part). This model considered that the influences on optimum sequences by assembly operations will be modified by the feedback from an interactive virtual environment. The authors of the article [63] selected the safety, efficiency and complexity as the optimization objectives.