Big Data Flow Adjustment Using Knapsack Problem

Modeling the 0-1 Knapsack Problem in Cargo Flow Adjustment

China’s railway network is one of the largest railway networks in the world. By the end of 2016, the total length of railway in operation reached 124,000 km and the annual freight volume exceeded 3.3 billion tons. However, the structure of network does not completely match transportation demand, i.e., there still exist a few bottlenecks in the network, which forces some freight flows to travel ...

Cancer's Big Data Problem

Greedy Algorithm 3 Knapsack Problem 3.1 Fractional Knapsack Problem

Greedy algorithm is a group of algorithms that have one common characteristic, making the best choice locally at each step without considering future plans. Thus, the essence of greedy algorithm is a choice function: given a set of options, choose the current best option. Because of the myopic nature of greedy algorithm, it is (as expected) not correct for many problems. However, there are cert...

Online Minimization Knapsack Problem

In this paper, we address the online minimization knapsack problem, i. e., the items are given one by one over time and the goal is to minimize the total cost of items that covers a knapsack. We study the removable model, where it is allowed to remove old items from the knapsack in order to accept a new item. We obtain the following results. (i) We propose an 8-competitive deterministic algorit...

A nonlinear Knapsack problem

The nonlinear Knapsack problem is to maximize a separable concave objective function, subject to a single "packing" constraint, in nonnegative variables. We consider this problem in integer and continuous variables, and also when the packing constraint is convex. Although the nonlinear Knapsack problem appears difficult in comparison with the linear Knapsack problem, we prove that its complexit...