LEADER 02328nam 2200445z- 450 001 9910637779003321 005 20221206 010 $a3-0365-5876-4 035 $a(CKB)5470000001631749 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/94566 035 $a(oapen)doab94566 035 $a(EXLCZ)995470000001631749 100 $a20202212d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aApplied (Meta)-Heuristic in Intelligent Systems 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (184 p.) 311 08$a3-0365-5875-6 330 $aEngineering and business problems are becoming increasingly difficult to solve due to the new economics triggered by big data, artificial intelligence, and the internet of things. Exact algorithms and heuristics are insufficient for solving such large and unstructured problems; instead, metaheuristic algorithms have emerged as the prevailing methods. A generic metaheuristic framework guides the course of search trajectories beyond local optimality, thus overcoming the limitations of traditional computation methods. The application of modern metaheuristics ranges from unmanned aerial and ground surface vehicles, unmanned factories, resource-constrained production, and humanoids to green logistics, renewable energy, circular economy, agricultural technology, environmental protection, finance technology, and the entertainment industry. This Special Issue presents high-quality papers proposing modern metaheuristics in intelligent systems. 517 $aApplied 606 $aHistory of engineering & technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $agreen energy 610 $ahyperheuristics 610 $alow carbons  610 $amatheuristics 610 $avehicle routing 610 $awireless networking 615 7$aHistory of engineering & technology 615 7$aTechnology: general issues 700 $aYin$b Peng-Yeng$4edt$01293396 702 $aYin$b Peng-Yeng$4oth 906 $aBOOK 912 $a9910637779003321 996 $aApplied (Meta)-Heuristic in Intelligent Systems$93040530 997 $aUNINA