An adapted discrete firefly algorithm for routing order pickers in manual warehouses

Warehouse management is a vital logistics activity that can affect supply chain costs. Of all the warehouse processes, order picking is one of the most time consuming and expensive, mainly due to the travel time spent by the picker to collect the different items of a generic picking list. In line with this consideration, this paper shows the application of a metaheuristic algorithm for routing order pickers in manual warehouses and minimizing the total distance covered. The proposed approach is an adaptation of the Discrete Firefly Algorithm (DFA), a nature-inspired algorithm based on the flashing behaviour of fireflies. The algorithm, developed under Microsoft Excel™, is then tested on an assumptive warehouse by taking into account ten picking lists composed of ten items, small number allowing the exact solution to be identified by examining the whole set of possible combinations and, accordingly, be compared with DFA solutions. Furthermore, results are also compared with those obtained from different heuristic routing policies (traversal, return and largest gap), from a heuristic algorithm commonly used for the vehicle routing problem (i.e. the Clarke and Wright saving algorithm) and from a metaheuristic algorithm namely the Water Wave Optimization (WWO). The computational analysis demonstrates that the proposed algorithm is generally able to provide better results than the heuristic routing policies and the heuristic algorithm examined; moreover, the adapted DFA procedure is always able to identify the optimal solution for the problem investigated.