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Risk efficiency of optimal water allocation within a single- and multi-stage decision-making framework

Madende, Primrose; Grové, Bennie - In: Agrekon 59 (2020) 1, pp. 78-92

Persistent link: https://www.econbiz.de/10012177598

Maximum Irrigation Benefit Using Multiobjective Differential Evolution Algorithm (MDEA)

Adeyemo, Josiah Adetayo - 2013

maximization of irrigation benefit in the lower orange catchment of South Africa. The two strategies presented are MDEA1 and MDEA3 … the two algorithms to find the better algorithm for the irrigation model presented. From the analysis of the results, the … exponential crossover method. The average total irrigation water of 104 Mm3 was generated with the corresponding averages of 32 …

Persistent link: https://www.econbiz.de/10013094398

Comparison of some heuristic algorithms for the flow shop problem with parallel machines to minimize the total earliness, tardiness and waiting time

Janiak, Adam; Lichtenstein, Maciej - In: Operations research proceedings 2000 : selected papers …, (pp. 378-383). 2001

Persistent link: https://www.econbiz.de/10001571664

Multi agent systems for multi enterprise scheduling

Spath, Dieter; Lanza, Gisela; Herm, Markus - In: Digital enterprise challenges : life-cycle approach to …, (pp. 475-485). 2002

Persistent link: https://www.econbiz.de/10001698349

Zur Konzeption der Retrograden Terminierung mit Personalzuordnung auf Basis eines genetischen Algorithmus

Kunz, Thomas - 2003

Persistent link: https://www.econbiz.de/10001876085

A genetic algorithm for the multi-class contingent bidding model

Watanapa, Bunthit; Techanitisawad, Anulark - In: OR spectrum : quantitative approaches in management 27 (2005) 4, pp. 525-549

Persistent link: https://www.econbiz.de/10003024038

Sequencing and lot-size optimisation of a production-and-inventory-system with multiple items using simulation and parallel genetic alghorithm

Kämpf, Michael; Köchel, Peter - In: Operations research proceedings 2004 : selected papers …, (pp. 102-109). 2005

Persistent link: https://www.econbiz.de/10002945952

Evolutionary Algorithm Parameter Fitness : An Exploratory Study

Manikas, Andrew; Godfrey, Michael - 2012

Genetic algorithms were the first evolutionary algorithm designed. These algorithms simulate natural selection to produce good solutions quickly for complex problems. Job shop scheduling with sequence dependent setup times is an NP-hard problem – any algorithm to optimize this problem has an...

Persistent link: https://www.econbiz.de/10014176148

Improving School Timetabling Using Genetic Algorithm

Al-Amoush, Farhan R. - 2011

Genetic Algorithm (GA) is one of the most popular optimization solutions. It has been implemented in various applications such as scheduling. Badly designed timetables are not just inconvenient but proved expensive in terms of wasting time and money. The flows of GA are using selection,...

Persistent link: https://www.econbiz.de/10014043274

Scheduling Algorithms for Flexible Flowshops : Worst and Average Case Performance

Sriskandarajah, Chelliah; Sethi, Suresh - 2019

We discuss the performance of scheduling algorithms for a certain kind of manufacturing environment, called the "Flexible Flowshop", which consists of a certain number of machine centers. Each center has one or more identical parallel machines. Each part is processed by at most one machine in...

Persistent link: https://www.econbiz.de/10014219051