This study describes a pickup and delivery vehicle routing problem, considering time windows in reality. The problem of tractor truck routes is formulated by a mixed integer programming model. Besides this, three algorithms - a guided local search, a tabu search, and simulated annealing - are proposed as solutions. The aims of our study are to optimize the number of internal tractor trucks used, and create optimal routes in order to minimize total logistics costs, including the fixed and variable costs of an internal vehicle group and the renting cost of external vehicles. Besides, our study also evaluates both the quality of solutions and the time to find optimal solutions to select the best suitable algorithm for the real problem mentioned above. A novel mathematical model is formulated by OR tools for Python. Compared to the current solution, our results reduced total costs by 18%, increased the proportion of orders completed by internal vehicles (84%), and the proportion of orders delivered on time (100%). Our study provides a mathematical model with time constraints and large job volumes for a complex distribution network in reality. The proposed mathematical model provides effective solutions for making decisions at logistics companies. Furthermore, our study emphasizes that simulated annealing is a more suitable algorithm than the two others for this vehicle routing problem.

Supply chain structure of global enterprises tend to develop dramatically. These lead to more difficulty for enterprises in managing and building information sharing systems. Thus, it is a necessary for enterprises to limit the scope of the information sharing system by selecting essential partners. The aims of this study are to quantify the cooperation of each supply chain member, and evaluate and visualize their effects in information sharing systems in order to support policymakers in making their decisions in supply chain management. The network analytical method in network science is applied to indicate the relationship between supply chain members and present a comprehensive supply chain visually. Moreover, Motor Corporation’s topology in Japan is used as a representation of global enterprise features to analyze the relationships between supply chain members. The data for Motor Corporation is secondary data which includes the number of suppliers, manufacturers, and dealers, and the interaction among them. Data is collected and verified from reputable websites such as www.marklines.com, or www.statista.com. As a result, this study contributes by applying a new method for not only determining the impact levels of supply chain members but also giving visual descriptions of impact levels on the large-scale information sharing system.

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