Integration of order preparation process in warehouse and distribution to production lines to minimize cost with adaptive whale algorithm approach

One of the most costly logistics activities is the picking process in the warehouse. Considering the internal logistics aspects, due to the limitations and resources available in order to reduce costs by increasing the level of capability, the supply systems of materials and components will be achieved along the line. Considering the effect of the completion time of pick operations on the start time of distribution operations and the cost of order preparation tardiness, the present study aimed to investigate a new issue related to the integrated process of order preparation in the warehouse and delivery on time to minimize cost according to the data of a car companys. In this regard, an integer nonlinear programming model is proposed to minimize the costs caused by tardiness. In order to validate the model, the small problem is solved in exact way. To solve the model, since the problem is NP-Hard, the method of whale optimization algorithm was used and to improve the optimal routing solutions, the problem was investigated by designing an adaptive whale algorithm considering the cost and time of visiting workstations as a fitting function. Also, to assess the proposed adaptive whale algorithm, the results were compared with two meta-heuristic algorithms of particle swarm optimization and gray wolf. The results show that the proposed adaptive wall algorithm performs better than other methods, which improves and reduces costs.