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Self-adapting genetic algorithms with an application to project scheduling
Hartmann, Sönke - 1999
This paper introduces a new general framework for genetic algorithms to solve a broad range of optimization problems. When designing a genetic algorithm, there may be several alternatives for a component such as crossover, mutation or decoding procedure, and it may be difficult to determine the...
Persistent link: https://www.econbiz.de/10011734932
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Theory
Sprecher, Arno; Drexl, Andreas - 1996
Persistent link: https://www.econbiz.de/10011806934
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Computation
Sprecher, Arno; Drexl, Andreas - 1996
Persistent link: https://www.econbiz.de/10011806935
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Solving the RCPSP efficiently at modest memory requirements
Sprecher, Arno - 1996
Persistent link: https://www.econbiz.de/10011787442
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Two sequencing problems: equivalence, optimal solution, and state-of-the-art results
Creemers, Stefan - 2017
Persistent link: https://www.econbiz.de/10011799026
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Scheduling Markovian PERT networks to maximize the net present value : new results
Hermans, Ben; Leus, Roel - 2017
Persistent link: https://www.econbiz.de/10011799039
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A massively parallel exact solution algorithm for the balanced minimum evolution problem
Catanzaro, Daniele; Frohn, Martin; Gascuel, Olivier; … - 2023
Persistent link: https://www.econbiz.de/10013486248
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Conference scheduling : a personalized approach
Vangerven, B.; Ficker, A.; Goossens, Dries; Passchyn, W.; … - 2017
Persistent link: https://www.econbiz.de/10011674170
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Interview scheduling : an integer programming approach
Braathen, Christian - 2022
Persistent link: https://www.econbiz.de/10013190837