https://www.google.co.id/intl/en/about/products?tab=rhDate of publication xxxx 00, 0000, date of current version xxxx 00, 0000.

Customers’ expectations of timely and accurate delivery and pickup of online purchases pose a new challenge to last-mile delivery. When the goods sent to customers are not received, they must be returned to the warehouse. This situation provides a high additional cost. Parcel locker systems and convenience stores have been launched to solve this problem and serve as pickup and payment stations. This research investigates a new last-mile distribution problem in the augmented system with three service modes: home delivery and pickup, parcel locker delivery and pickup, and home or parcel locker delivery and pickup. Previously, the simultaneous delivery and pickup problem with time windows (SDPPTW) only considered delivery and pickup to customers. The new problem proposed in this research addresses additional locker pickup and delivery options. The proposed problem is called the vehicle routing problem with simultaneous pickup and delivery and parcel lockers (VRPSPDPL). This research formulated a new mathematical model and developed two simulated annealing (SA) algorithms to solve the problem. The goal is to minimize the total traveling cost. Since there are no existing benchmark instances for the problem, we generate new instances based on SDPPTW benchmark instances. The experimental results show that the proposed algorithms are effective and efficient in solving VRPSPDPL.

Municipal waste management has become a challenging issue with the rise in urban populations and changes in people’s habits, particularly in developing countries. Moreover, government policy plays an important role associated with municipal waste management. Thus, this research proposes the regional location routing problem (RLRP) model and multi-depot regional location routing problem (MRLRP) model, which are extensions of the location routing problem (LRP), to provide a better municipal waste collection process. The model is constructed to cover the minimum number of depot facilities’ policy requirements for each region due to government policy, i.e., the large-scale social restrictions in each region. The goal is to determine the depot locations in each region and the vehicles’ routes for collecting waste to fulfill inter-regional independent needs at a minimum total cost. This research conducts numerical examples with actual data to illustrate the model and implements a hybrid genetic algorithm and simulated annealing optimization to solve the problem. The results show that the proposed method efficiently solves the RLRP and MRLRP.

This research aims to improve energy sustainability in transportation management. The case was derived from port-to-port coal transportation problem commonly faced by third-party logistic (3PL) company. During planning, they must determine which shipsets to be used and assign them to the loading/unloading berths. Each berth varies in terms of its loading/unloading speed and each shipset varies in terms of its capacity, sail speed, and fuel consumption rate. The selection of shipset impacts the auxiliary and main engine fuel consumption while the selection of berth impacts only the auxiliary engine fuel consumption. The target is to minimize the total fuel consumed by both engines for the whole shipset. We modelled the case through Multiple Vehicle Allocation Problem (MVAP) framework and proposed a heuristic algorithm to find the solutions. The heuristic algorithm is proven to be able to reach an optimal solution for small cases and near-optimal for medium to large cases.