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Implementing green projects is critical to achieve the green and sustainable development goal. This paper investigates a green project planning with the realistic consideration of multiple objectives including minimizing the total cost and maximizing the total emission reduction. The realistic multi-objective problem in engineering optimization aims to find a best solution for real-world use instead of finding a set of Pareto-optimal solutions. To handle this problem, we develop a weight sets-based multi-objective evolutionary optimization approach to find the best solution for realistic use. The approach integrates a single-objective evolutionary optimization process, novel solution encoding and decoding heuristics, and a non-dominated sort technique. Based on real-world data from a seaport in China, experiments were conducted to validate the proposed optimization approach. Results show that the proposed approach can effectively solve the real-world multi-objective green project planning problem because the solution found by our approach is one of the Pareto optimal solutions generated by the NSGA-II.

Green Project Planning with Realistic Multi-Objective Consideration in Developing Sustainable Port