Abstract
Worker assignment is a relatively new problem in assembly lines that typically is encountered in situations in which the workforce is heterogeneous. The optimal assignment of a heterogeneous workforce is known as the assembly line worker assignment and balancing problem (ALWABP). This problem is different from the well-known simple assembly line balancing problem concerning the task execution times, and it varies according to the assigned worker. Minimal work has been reported in worker assignment in two-sided assembly lines. This research studies worker assignment and line balancing in two-sided assembly lines with an objective of minimizing the cycle time (TALWABP). A mixed-integer programming model is developed, and CPLEX solver is used to solve the small-size problems. An improved migrating birds optimization algorithm is employed to deal with the large-size problems due to the NP-hard nature of the problem. The proposed algorithm utilizes a restart mechanism to avoid being trapped in the local optima. The solutions obtained using the proposed algorithms are compared with well-known metaheuristic algorithms such as artificial bee colony and simulated annealing. Comparative study and statistical analysis indicate that the proposed algorithm can achieve the optimal solutions for small-size problems, and it shows superior performance over benchmark algorithms for large-size problems.
Highlights
Lines are utilized extensively in manufacturing to produce standardized products in a process in which a set of tasks is divided among workstations, and each workstation is assigned workers to perform the allocated tasks (Oksuz et al 2017)
Roshani and Giglio (2017) addressed a new problem named Multi-manned Assembly Line Balancing Problem (MALBP) in which there is the possibility of assigning more than one operator to each workstation according to the product features with the objective of minimizing cycle time for a given number of workstations; they developed a new mathematical model for solving the proposed problem
As reported in Janardhanan et al (2018) and Li et al (2016a), this paper proposes the following iteration mechanism for cycle time update and decoding procedure and proposes two procedures (Procedure 1 and Procedure 2)
Summary
Lines are utilized extensively in manufacturing to produce standardized products in a process in which a set of tasks is divided among workstations, and each workstation is assigned workers to perform the allocated tasks (Oksuz et al 2017). Roshani and Giglio (2017) addressed a new problem named Multi-manned Assembly Line Balancing Problem (MALBP) in which there is the possibility of assigning more than one operator to each workstation according to the product features with the objective of minimizing cycle time for a given number of workstations; they developed a new mathematical model for solving the proposed problem. The proposed model employs one decision variable, ttii, to indicate the operation time of task i by the worker to whom this task is assigned Step 6: Select the assignable task, which is on the former position of the task permutation vector; allocate the task to the selected side, update the remaining capacity of the selected side, and go to Step 1
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