Abstract
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.
Highlights
In the trend of sustainable economy and low-carbon development, it is crucial to achieve the green development goal by implementing various green projects, which results in a very important decision-making problem, green project planning (GPP) problems
The GPP problem investigated in this paper is a special project planning and scheduling problem considering the green project construction and realistic multi-objective
This algorithm decomposes a multi-objective optimization problem into a number of single-objective optimization problems [33]. These methods cannot be directly used to handle the GPP problem investigated in this paper because different chromosome representations and genetic operators are required for different optimization problems. These multi-objective evolutionary algorithms avoid the determination of weights, and instead generate a set of Pareto optimal solutions
Summary
In the trend of sustainable economy and low-carbon development, it is crucial to achieve the green development goal by implementing various green projects, which results in a very important decision-making problem, green project planning (GPP) problems. This paper investigates a GPP problem with realistic multi-objective consideration in developing a sustainable port. The objectives of the investigated problem include maximizing the total CO2 emission reduction and minimizing the total project construction cost. To solve this problem, a weight sets-based multi-objective evolutionary optimization approach is proposed. This paper contributes the literature by: (1) effectively handling a novel green project planning problem with realistic multi-objective consideration in developing sustainable port; and (2) developing a weight sets-based multi-objective evolutionary optimization approach to solve realistic multi-objective optimization problems.
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