set a bi-objectives model for suppliers selection with capacity constraint and reducing lead-time with meta-heuristic algorithms

Supplier evaluation and selection are some of the essential issues in organizational strategic planning between managers and entrepreneurs. nodaway, markets are in a situation where both buyers and suppliers are under the challenge. supplier selection is a complex problem, and decision-makers need to use mathematical models to solve it. in this paper, we present a bi-objective supplier-selection model. the first objective is minimizing the total annual cost, and the second is minimizing lead times. since supplier selection belongs to np. the hard category of problems and the model objectives have conflict, and we used three different multi-objective meta-heuristic algorithms to solve the presented model and compare the results of these algorithms. the solving algorithms are multi-objective invasive weed optimization (moiwo), non-dominated sorting genetic algorithm (nsga-ii), and non-dominated ranked genetic algorithms (nrga). the algorithm parameters were tuned using the taguchi method, and for comparing the algorithms, the topsis model has been used.