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Kamali et al. (2011) developed a multi-objective mixed nonlinear integer programming model for the first time to coordinate the system of single buyer and multi-vendors' multi-period with certain demand under all-unit quantity discount policy for vendors.
Yousefi-Babadi et al. (2017) proposed a multi-objectives mixed-integer non-linear programming (MINLP) model for a petrochemical supply chain under uncertainty environments, namely disruption risks and less knowledge of parameters.
This paper shows a multi-objectives mixed-integer non-linear programming (MINLP) model for a petrochemical supply chain under uncertainty environments, namely disruption risks and less knowledge of parameters.
The proposed ILP model has multi objectives cost function.
A novel multi objective optimization algorithm capable of handling a multitude of objectives in mixed integer nonlinear search space and a novel decision making methodology are integrated with a sequential modular process simulator to optimize processes with a multitude of objectives rigorously and efficiently.
This paper addresses the concept-based multi-objective problem by proposing two novel multi objective evolutionary algorithms.
His research interests include Data Envelopment Analysis DEAA), Fuzzy and Multi Objective Programming (MOP).
Amid et al. (2006) represented multi objective linear programming model to supplier selection.
This paper proposes a modified simulated annealing approach for solving multi objective facility layout problem.
In this paper, an ILP model with multi objective cost function is proposed.
To do so, the recent multi objective framework called MoMIR is employed.
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