| dc.description.abstract | It is undeniable that finding the best logistics solutions for customers is the main task of a service
provider, and this is never an easy thing. These solutions must be ideal and optimal in terms of
workload, cost, time, and other resources. This directly upgrades and adds value to a company's
supply chain. As a result, today's logistics organizations are always learning, developing, and
implementing new technology to add value to their businesses. Maximizing container volume
utilization is considered paramount for any business providing logistics services. Optimizing the
capacity of containers not only helps to rationally use logistics resources, saving time and
money, but also contributes to the sustainability of a business in this forever growing Logistics
industry. However, many existing solutions to the problem of container handling (CLP), there
are still trade-offs in each approach. Each person has their own characteristics, functions and
qualities, so it is necessary to carefully consider each specific case.
This thesis will illustrate on a hybrid approach to maximize container’s volume utilization, in the
mean time still satisfy other important constraints such as weight limit, cargo’s stability, weight
central distribution, … This thesis aims to apply Random Constructive Heuristics Algorithm and
Tabu Search into solving the container loading problem. And then compare the results with other
published studies. | en_US |
