An Application of Green Warehousing: Energy Minimizing Forklift Routing Problem

Arsham Atashi Khoei, Department of Industrial Engineering, METU


Material handling operations in warehouses involve picking and retrieving the orders or materials mostly using order pickers (order picker forklifts). The high frequency of this job in warehouses results in high energy consumption contribution of material handling in warehousing division of logistics. Therefore, the ways to reduce the energy consumption of order pickers can be interesting issues to be studied to follow green warehousing applications in logistics. To this end, we study the possibilities of routing the order pickers in an energy-efficient way. To the best of our knowledge, there is no study in the literature with explicit evaluation of the energy consumption of the order pickers to be minimized. The electric order picker forklifts are highly recognized machines in material handling systems of warehouses and are used in applications where pallet trucks, rolling ladders, and other piece-picking methods were traditionally used. Thanks to the technology used in these orders pickers, their maneuverability in very narrow aisles and high level picking capabilities enables the warehousing systems to take full advantage of limited storage space. We introduce the energy minimizing forklift routing problem (EMFRP) where an electric order picker forklift ridden by an operator is routed to pick the ordered items in a warehouse and bring them to the depot such that the total energy consumption of the forklift is minimized. We calculate the forklift's energy consumption considering the friction forces, the acceleration and deceleration of forklift and the load on the fork in both horizontal and vertical moves. We provide an MIP formulation to solve the EMFRP. This formulation has some characteristics of the traveling salesman problem formulation and is not able to solve large problem instances in reasonable time. Hence, we adapt the Held-Karp dynamic programming algorithm for the EMFRP as well, which solves instances with up to 25 orders in reasonable time. Due to the similarity of the EMFRP to the TSP, some TSP-based constructive and improvement heuristics, i.e., nearest neighbor algorithm, 2-opt and 3-opt algorithms, are adapted for the EMFRP to solve larger instances. Two problem based algorithms for constructing an initial tour and improving a given tour are also developed both subsuming the dynamic programming approach. The computational experiments are performed on instances generated based on warehouse schemes used in the literature. The provided experimental results show the solution quality of the heuristic approaches as well as the amount of energy savings when the EMFRP solutions are used. This study is supported by TÜBİTAK (the Scientific and Technological Research Council of Turkey) with project number 217M486.
joint work with Prof. Haldun Süral and Assist. Prof. Mustafa Kemal Tural

Short Bio

Arsham Atashi Khoei is a PhD student in Industrial Engineering Department of Middle East Technical University since February 2015. He received his BSc. and MSc. degrees in 2009 and 2012, from Industrial Engineering in Iran. Currently he is working at Industrial Engineering Department of TED University as a research assistant. His recent research areas include CO2 emission and energy consumption concerns in distribution systems and warehouses.


Friday, April 3, 2020, 4.00 pm
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