A Multi-Objective Network Optimization Problem
Abstract
This blog post addresses the design of a sustainable logistic network for GreenForwarder—a multinational freight company—by balancing profitability, environmental emissions, and regional reach. A multi-objective network optimization problem is formulated over a graph that represents cities and potential transport connections. Using a modified Minimum Spanning Tree (MST) algorithm that incorporates capacity constraints and investment costs, the approach has been inspired by the Steiner Tree Problem and evaluates candidate edges dynamically by considering cost, emission factors, and a bonus for expanding regional reach. POC and LIVE differ significantly in their approaches, particularly in their starting points. POC begins by simplifying the “full” graph and focusing on optimizing its objective function, whereas LIVE prioritizes satisfying its unique constraint from the outset. For the MVP, two methods are employed to determine which approach would yield a better outcome, as the significance of profit’s contribution was unknown during the project’s initial stages. Detailed experimental results, analysis, and comparisons are provided in later sections.
Tags: #Operations Research