Storage location assignment is part of the realworld problem of warehouse operating which considered an optimization problem. However, with the different properties of the product assigned and location of the various warehouses, a traditional optimization algorithm is not able to apply directly to solve the unique problem of each warehouse. Therefore, the location assignment problem at Lazada Thailand Warehouse, which has exclusive properties and rich constraints, requires a specific designed optimization algorithm in order to acquire a feasible solution. This paper proposes the Multiobjective Optimization using Flower Pollination Algorithm (MOFPA) for Storage Location Assignment at Lazada Thailand Warehouse, which introduces new operators and multiobjective fitness functions to cope with more complex constraints. The experimental results on the 4 real datasets of Lazada Thailand Warehouse show that MOFPA is capable of finding solutions for almost all datasets, and it also outperforms the traditional generic algorithm for all datasets.
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