... algorithm (GA) to optimise our formal model to allocate and schedule tasks to analysts. The proposed solution is able to allocate tasks to analysts with appropriate skills and experience, while taking into account staff well-being objectives. Findings They demonstrate their GA model outperforms baseline...

... planning horizon similar to the dynamic facility layout problem. A hybrid genetic algorithm-based approach integrated with local search heuristic methods is also proposed to improve the solution. Findings This paper finds that the DPLP model is effective in modeling the changing layout of a digital...

... graph for the characterization of contemporaneous causality among the 10 indices. Findings The PC algorithm identifies the causal pattern, and the linear non-Gaussian acyclic model algorithm further determines the causal path from which we perform innovation accounting analysis. Sophisticated price...

..., we perform the calibration of our models through simulated and actual data from the Fish Pool with accompanying model validation diagnostics. Finally, Section 5 concludes. Algorithms Decision support systems Forecasting Markov chain Price data Fisheries Multi-factor model Regime-switching...

...Dharyll Prince Mariscal Abellana; Paula Esplanada Mayol Purpose This paper aims to propose a novel hybrid-decision-making trial and evaluation laboratory-K means clustering algorithm as a decision-making framework for analyzing the barriers of green computing adoption. Design/methodology...

... two algorithms, namely, multi-objective genetic and multi-objective particle swarm. In this research, to integrate sustainable supplier selection and optimization of sustainability performance indicators in supply chain network design considering minimization of cost and time and maximization...

... that the results obtained from the colonial competition algorithm have higher quality than the genetic algorithm. This quality of results includes relative percentage deviation and computational time of the algorithm and it is shown that the computational time of the colonial competition algorithm is significantly...

...Mazin A.M. Al Janabi Purpose This study aims to examine the theoretical foundations for multivariate portfolio optimization algorithms under illiquid market conditions. In this study, special emphasis is devoted to the application of a risk-engine, which is based on the contemporary concept...

...Levi Ribeiro de Abreu; Bruno de Athayde Prata Purpose The purpose of this paper is to present a hybrid meta-heuristic based on genetic algorithms (GAs), simulated annealing, variable neighborhood descent and path relinking for solving the variant of the unrelated parallel machine scheduling...

... (MSRCPSP) for investigation. The objective is the minimization of the makespan or total project duration. Design/methodology/approach To solve this complex problem, the authors propose a teaching–learning-based optimization (TLBO) algorithm in which self-study and examination have been used...

... level, economic structure, population, urbanization, technological progress, regulations and policies, air temperature and electricity price. According to the data availability, this paper selects nine variables as the predictors for electricity demand forecasting as follows: Planning Algorithms...

... as the base of the earned attention measure. An evolutionary algorithm – a memetic algorithm – is applied to identify strategies that aim to maximize earned attention. Computational analysis is performed resorting to simulated data, and the memetic algorithm is assessed through the comparison with a standard...

... Nassim Dehouche can be contacted at: nassim.dehouche@mahidol.ac.th 02 09 2015 21 11 2015 28 12 2015 © Emerald Publishing Limited 2017 Emerald Publishing Limited Licensed re-use rights only Decision making Algorithms SWOT Management Strategy Modelling...