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    Energy optimal path finding for waste collection robot using ant colony optimization algorithm
    (2021-01-01)
    Tomitagawa, Koki
    ;
    Chotiphan, Supannada
    ;
    Kuchii, Shigeru
    ;
    Anuntachai, Anuntapat
    ;
    Wongwirat, Olarn
    Solid Waste Management (SWM) has always been an important consideration for any country, and among the operational steps of SWM, Solid Waste Collection (SWC) has become one of the most challenging ones. Currently, most of the vehicles used for waste collection require workers and have the problem of emitting CO2. Compared to waste collection by vehicles, waste collection using mobile robots has the advantage of not consuming personnel and not emitting CO2, which is harmful to the environment. However, while mobile robots can solve the shortage of manpower and environmental problems, they also have the problem of limited energy resources. In order for mobile robots to collect waste more efficiently, we designed the waste collection problem as a Capacitated Vehicle Routing Problem (CVRP) and optimized it using the Ant Colony Optimization (ACO) algorithm. The ACO algorithm proposed in this study focuses on the energy consumption of the mobile robot performing waste collection and searches for a route with less energy consumption by using the waste weight as the weighting factor. The preliminary performance verification of the proposed method is compared with the existing conventional ACO algorithm using the CVRP benchmark.
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    Routing algorithm in warehouse with congestion consideration using an ACO with VLC support
    (2017-10-19)
    Srivilas, Krit
    ;
    Cherntanomwong, Panarat
    For warehouse management, order picking is one of the most important factors since it is the most time consuming operation contributing to the overall warehouse operational cost. Moreover, if the picking congestion occurs when there are multiple order pickers, the consumed picking time will increase. Therefore, this paper presents the new routing algorithm to reduce the picking time for multiple pickers. The proposed routing algorithm is based on an Ant Colony Optimization (ACO) combined with the indoor positioning supported by the Visible Light Communication (VLC) system. To validate the proposed algorithm, the experiment is done in the multiple-block picker-To-part warehouse of the construction material supplier. The experimental results show that the proposed routing algorithm is able to reduce the travelling time leading to reduce the order picking time.