7 research outputs found
Using the idea of expanded core for the exact solution of bi-objective multi-dimensional knapsack problems
Knapsack problem, Multi-objective programming, Core, Exact algorithm,
Phosphorylation state of red and white muscle in tilapia during graded hypoxia: an in vivo 31
Hybrid Metaheuristics for Multi-objective combinatorial optimization
Many real-world optimization problems can be modelled as combinatorial optimization problems. Often, these problems are characterized by their large size and the presence of multiple, conflicting objectives. Despite progress in solving multi-objective combinatorial optimization problems exactly, the large size often means that heuristics are required for their solution in acceptable time. Since the middle of the nineties the trend is towards heuristics that “pick and choose” elements from several of the established metaheuristic schemes. Such hybrid approximation techniques may even combine exact and heuristic approaches. In this chapter we give an overview over approximation methods in multi-objective combinatorial optimization. We briefly summarize “classical” metaheuristics and focus on recent approaches, where metaheuristics are hybridized and/or combined with exact methods