A differential evolution algorithm for the capacitated VRP with flexibility of mixing pickup and delivery services and the maximum duration of a route in poultry industry

In this paper, we propose two heuristics to solve the general q-delivery vehicle routing problem with consideration of flexibility of mixing pickup, delivery services and a maximum duration of a route constraint which is the extending version of the well-known vrp with pickup and delivery problem. firstly, the heuristic called de_g-q-dvrp-fd is presented to determine the routing of transferring pullets from pullet houses to hen houses. since the problem considered is very complicated, the de_g-q-dvrp-fd is extended to the two-phase heuristic called mesomde_g-q-dvrp-fd. the difference between two heuristics is that in the mesomde_g-q-dvrp-fd algorithm, the customer vertices (pullet houses) will be clustered before determining routes. the clustering of customer vertices method called the multifactor based evolving self-organizing map is proposed in the first phase in order to completely utilize the vehicle. finally, in the second phase, the de_g-q-dvrp-fd is used to execute the routing. to demonstrate the algorithm efficiency, flock allocation from pullet houses to hen houses in the egg industry is used as the case study. the results obtained from this study show that the mesomde_g-q-dvrp-fd algorithm provides lower total cost values than that of the firm’s current practice by 7.59–31.28 and 0.84–13.15 % better than the de_g-q-dvrp-fd algorithm. additionally, the mesomde_g-q-dvrp-fd is adjusted to solve the benchmark problem found in the literature. the experimental results show that the mesomde_g-q-dvrp-fd algorithm yields better total cost values by 5.72–61.60 % (with an average of 31.46 %).