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. (C) 2015 Elsevier Ltd. All rights reserved.
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Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Tsinghua Univ, Grad Sch Shenzhen, Div Logist & Transportat, Shenzhen 518055, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
Xiang Xi
Liu Changchun
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Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R ChinaTsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
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Univ Vienna, Dept Business Adm, Oskar Morgenstern Pl 1, A-1090 Vienna, AustriaUniv Vienna, Dept Business Adm, Oskar Morgenstern Pl 1, A-1090 Vienna, Austria
Matl, Piotr
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Nolz, Pamela C.
Ritzinger, Ulrike
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Austrian Inst Technol, Mobil Dept Dynam Transportat Syst, Giefinggasse 2, A-1210 Vienna, AustriaUniv Vienna, Dept Business Adm, Oskar Morgenstern Pl 1, A-1090 Vienna, Austria
Ritzinger, Ulrike
Ruthmair, Mario
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Univ Vienna, Dept Stat & Operat Res, Oskar Morgenstern Pl 1, A-1090 Vienna, AustriaUniv Vienna, Dept Business Adm, Oskar Morgenstern Pl 1, A-1090 Vienna, Austria