A hybrid meta-heuristic approach for design and solving a location routing problem Considering the time window

The supply chain requires a distribution network between customers and suppliers. This distribution network can be multifaceted. Combining these two problems into a single problem increases the efficiency of the distribution network and ultimately increases the efficiency of the supply chain. Establishing a window of time to deliver goods to customers also increases their satisfaction and, as a result, more profitability in the long run. Therefore, in this research, an attempt has been made to present a routing-location problem in the multimodal transportation network. A time window is also included in this model. To solve such a model, especially in large dimensions, exact solution methods cannot be used. Based on this, a combined meta-heuristic algorithm (genetic optimization algorithm and neural network) has been proposed to solve the model, and the result has been compared with two gray wolf optimization algorithms and grasshopper optimization algorithms. The presented results indicate the effectiveness of the proposed algorithm.

Keywords:

The problem of routing - locating , Time window , Meta-heuristic algorithm of gray wolf optimization , Meta-heuristic algorithm of locust optimization , Hybrid meta-heuristic algorithm