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Showing 2 results for Multi-Objective Model

Mostafa Setak, Samaneh Sharifi,
Volume 22, Issue 4 (12-2011)
Abstract

In recent years, Supplier evaluation and selection, an important element in supply chain management, has been gaining attention in both academic literature and industrial practice. The Mixed integer multi-Objective non-Linear programming model (MIMONLP) presented in this paper aimed to evaluate and select the appropriate set of suppliers considering quantitative and qualitative criteria and in addition to selecting the first layer's suppliers which relate directly to the organization, analyses the characteristics of second-layers suppliers, and design a network to determine the flow rate of products and materials between buyers and best suppliers in both layers. Another important feature of this model is considering holding costs of different products over the planning horizon and quantity discounts for the first layer's suppliers at the same time. Finally, the model is solved by using goal programming approach and numerical examples are presented to test the performance of proposed model.


Saeed Dehnavi, Ahmad Sadegheih,
Volume 31, Issue 1 (3-2020)
Abstract

In this paper, an integrated mathematical model of the dynamic cell formation and production planning, considering the pricing and advertising decision is proposed. This paper puts emphasis on the effect of demand aspects (e.g., pricing and advertising decisions) along with the supply aspects (e.g., reconfiguration, inventory, backorder and outsourcing decisions) in developed model. Due to imprecise and fuzzy nature of input data such as unit costs, capacities and processing times in practice, a fuzzy multi-objective programming model is proposed to determine the optimal demand and supply variables simultaneously. For this purpose, a fuzzy goal programming method is used to solve the equivalent defuzzified multi-objective model. The objective functions are to maximize the total profit for firm and maximize the utilization rate of machine capacity. The proposed model and solution method is verified by a numerical example.

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