Optimal Workers Allocation for the Crossdocking Just in Time Scheduling Problem
Álvarez Pérez, Guillermo A.
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In this work, a warehouse is allowed to function as a crossdock to minimize costs for a scheduling problem. These costs are due to two factors: the number of teams of workers hired to do the job, and the transit storage time for cargo. Each team of workers has a fixed cost per working day, and the cargo can incur early and tardy delivery costs. Then, the transit storage time for cargo is minimized according to Just in Time (JIT) scheduling. The goal is to obtain both: the optimal number of teams of workers in the crossdock and a schedule that minimizes the transit storage time for cargo. An integrated model to obtain both the optimal number of teams of workers and the schedule for the problem is written. The model uses the machine scheduling notation to describe it. Since the problem is known as NP-hard, a solution approach based on a combination of two metaheuristics, Reactive GRASP embedded in a Local Search algorithm and Tabu Search (RGLSTS), is provided. The results obtained from the exact method that uses the ILOG CPLEX 9.1 solver for 14 problem instances and the results obtained from the RGLSTS metaheuristic algorithm for the same problem instances are discussed. This research has an important academic contribution because it involves the development of a metaheuristic algorithm not previously applied to a relevant problem that has not received attention. Besides, the source codes of the programs that solve the problem are available for the reader and they can be modified according to the user needs. In the industry field, the algorithm mentioned above can be easily adapted in order to be applied to a real problem (i.e., large transshipments in companies like Wal-Mart, HEB, among others). Obtaining optimal or near optimal solutions for the problem of this work represents an improvement in the movement or distribution of the workforce and products, reducing this way, hiring costs, transportation costs and inventory costs.