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In this study we propose a threshold accepting based hyperheuristic for solving in a single run both the resource-constrained project scheduling problem or resource allocation, and the resource leveling problem. Having their roots in the field of artificial intelligence, hyperheuristics operate in the “low-level” heuristics domain rather than in the solutions domain. The hyperheuristic has been implemented within a commercial project management software package. Low-level heuristics operate on the solution domain defined by the priority values that the software uses for resource allocation. A case example from the literature and computational experiments on randomly generated projects demonstrate that the hyperheuristic achieves good performance in a timely manner, improving the results provided by the software. [ABSTRACT FROM AUTHOR]

The greedy randomized adaptive search procedure (GRASP) is a well-known computational procedure for handling combinatorial optimization problems. Hyperheuristics, or heuristics to choose heuristics, are higher-level algorithms that operate on low-level heuristics, which in turn work in the solution domain. In this paper, a GRASP-inspired hyperheuristic is proposed for solving the resource-constrained project scheduling problem (RCPSP), one of the most important challenges facing construction project schedulers. The hyperheuristic is the main component of a multilevel procedure that runs within a commercial project management software system. On the basis of simple moves such as 'swap' and 'replace,' the low-level heuristics operate on the priority values that the software uses for scheduling activities. The efficiency of this prioritization-based algorithm has been addressed through a series of computational experiments on randomly generated projects. Moreover, the proposed procedure shows the advantages of utilizing the hyperheuristic approach to deal with optimization problems in the construction field. [ABSTRACT FROM AUTHOR]

When decentralized strategies are considered for managing wastewater, natural systems for wastewater treatment (NSWT) (constructed wetlands) seem to be strongly preferred in comparison with the conventional activated sludge wastewater treatment systems. However, because of their high land requirements, land-use suitability analysis should be conducted to specify adequate areas for their accommodation. Multicriteria spatial decision support systems have emerged as the technology that takes into account both decision criteria and constraints in complex land-use planning problems. This study presents a multiattribute decision analysis approach called the spatial fuzzy Analytic Hierarchy Process (SFAHP) to support raster-based land-use suitability studies for the implementation of NSWT. The SFAHP enables decision makers to circumvent vagueness when they perform evaluations using linguistic variables. Its application in a region of Northeastern Greece using a two-level criteria hierarchical model demonstrates its potential use for suitability analyses. [ABSTRACT FROM AUTHOR]