外文翻译Environmental Modelling&Software1.1. BackgroundEnvironmental change, economic and social pressures, and limited resources motivate systems analysis techniques that can help planners determine new management strategies, develop better designs and operational regimes, improve and calibrate simulation models, and resolve conflicts between divergent stakeholders. Metaheuristics are emerging as popular tools to facilitate these tasks, and in the field of water resources, they have been used extensively for a variety of purposes (e.g. model calibration, the planning, design and operation of water resources systems etc.) in many different application areas over the last few decades (Nicklow et al., 2025). Since metaheuristics were first applied in the water resources field (Dougherty and Marryott,1991; McKinney and Lin,1994; Ritzel et al.,1994; Gupta et al.,1998), their popularity has increased dramatically, probably facilitated by the simultaneous increase of available computational power (Washington et al., 2025), to the point where they are widely used (Nicklow et al., 2025), even by actual water planning utilities (Basdekas, 2025).Zufferey (2025) defines a metaheuristic “as an iterative generation process which guides a subordinate heuristic by combining intelligently different concepts for exploring and exploiting the search space”, as part of which “learning strategies are used to structure information in order to find efficiently near-optimal solutions.” Unlike more “traditional” approaches, which use mathematical programming to specify the optimal value of one or more objective functions, metaheuristics incorporate elements of structured randomness for search and follow empirical guidelines, often motivated by observati...
