.... Findings Computational results show that the mini-batch k-means algorithm can generate up to 20,000 high-quality clusters with limited computational effort, enabling precise and efficient targeting. Moreover, the proposed linear programming model can be solved within reasonable time even at this scale...

... aid (MCDA) can assist the investment portfolios formation, increasing the reliability of decision-making, presents an opportunity for improvement through linear programming methodologies with the objective of optimizing the results, as the results obtained with the model were not optimized...

... at: mahmoud.kamel@fcom.bu.edu.eg λ j ≥ 0 j = 1 , 2 , … , n . e λ = 1 Financial performance Data envelopment analysis (DEA) Artificial neural networks (ANN) Banks Egypt Benchmarking Linear programming Neural networks where: θ = output-oriented efficiency...

... chain network under an uncertain environment and different scenarios is also developed. Design/methodology/approach In this paper, we combined grey linear programming (GLP) and fuzzy set theory to present a solution approach for the problem. The proposed model first solves the given problem using...

..., a binary multi-objective linear programming approach was developed to select the risk response strategies, and an augmented e-constraint method (AECM) was used. Findings Regarding the project triple well-known constraints of time, cost and quality, which organizations usually confront, the HSE risks...

... 19 05 2020 30 05 2020 © Emerald Publishing Limited 2021 Emerald Publishing Limited Licensed re-use rights only Humanitarian logistics Vehicle routing problem Network flow problem Redistribution Fairness in supply Logistics Optimization Linear programming Routing...

... which are required to transport a preempted job from one machine to another. This study considers the case when the transportation delays are variable. Design/methodology/approach The contribution is twofold. First, this study proposes a new linear programming formulation in real and binary decision...

... Security Act. Liansheng Larry Tang can be contacted at: tangstat@gmail.com 05 11 2018 30 03 2019 16 06 2019 © Emerald Publishing Limited 2019 Emerald Publishing Limited Licensed re-use rights only Performance management Efficiency analysis Linear programming...

... and distribution centers around cities can apply this model to optimize their logistic systems. Figure 1. Schematic of the developed problem Logistics Linear programming Heuristics Inventory control Facility layout Among the different classifications of perishable goods, some...

... network for controlling the coal blending process in iron and steel plants. Yin et al. (2000) integrated a mixed-discrete variable optimization model with artificial neural network to solve a non-linear programming problem for arriving at the optimal coal blending decision. Various coal...

.... Selection is done based on the performance values of the vendors on certain predefined criteria. Design/methodology/approach An integrated approach involving data envelopment analysis (DEA), technique for order of preference by similarity to ideal solution (TOPSIS) and linear programming (LP) problem...