Bi-objective optimisation model for installation scheduling in offshore wind farms. (February 2017)

• Record Type: Journal Article
• Authors: Irawan, Chandra Ade; Jones, Dylan; Ouelhadj, Djamila
• Is Part Of: Computers & operations research. Volume 78(2017)
• Page Start: 393
• Page End: 407
• Publication Date: 2017-02
• Subjects: Variable Neighbourhood Search -- Simulated Annealing -- Multi-objectives -- Compromise programming -- Installation scheduling -- Offshore wind farm; Operations research -- Periodicals; Electronic digital computers -- Periodicals; 004.05
• DOI: 10.1016/j.cor.2015.09.010
• Languages: English
• ISSNs: 0305-0548

Abstract

Abstract: A bi-objective optimisation using a compromise programming approach is proposed for installation scheduling of an offshore wind farm. As the installation cost and the completion period of the installation are important aspects in the construction of an offshore wind farm, the proposed method is used to deal with those conflicting objectives. We develop a mathematical model using integer linear programming (ILP) to determine the optimal installation schedule considering several constraints such as weather condition and the availability of vessels. We suggest two approaches to deal with the multi-objective installation scheduling problem, namely compromise programming with exact method and with metaheuristic techniques. In the exact method the problem is solved by CPLEX whereas in the metaheuristic approach we propose Variable Neighbourhood Search (VNS) and Simulated Annealing (SA). Moreover, greedy algorithms and a local search for solving the scheduling problem are introduced. Two generated datasets are used for testing our approaches. The computational experiments show that the proposed metaheuristic approaches produce interesting results as the optimal solution for some cases is obtained. Highlights: Development of a mathematical model of the installation scheduling problem. Construction of greedy algorithms and a local search for finding the best schedule. Application and comparison of VNS and SA for solving the scheduling problems.