Browsing by Author "Chedid J.A."

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A three layer supply chain model with multiple suppliers, manufacturers and retailers for multiple items
(2014) Sana S.S.; Chedid J.A.; Navarro K.S.
The replenishment size/production lot size problem both for perfect and imperfect quality products studied in this paper is motivated by the optimal strategy in a three layer supply chain consisting of multiple suppliers, manufacturers and retailers. In this model, each manufacturer produces each product with a combination of several raw materials which are supplied by each supplier. The defective products at suppliers and manufacturers are sent back to the respective upstream members at lower price than the respective purchasing price. Finally, the expected average profits of suppliers, manufacturers and retailers are formulated by trading off set up costs, purchasing costs, screening costs, production costs, inventory costs and selling prices. The objective of this chain is to compare between the collaborating system and Stakelberg game structure so that the expected average profit of the chain is maximized. In a numerical illustration, the optimal solution of the collaborating system shows a better optimal solution than the approach by Stakelberg. © 2013 Elsevier Inc. All rights reserved.
An inventory model of three-layer supply chain of wood and furniture industry in the Caribbean region of Colombia
(Taylor and Francis, 2018) Salas Navarro K.; Chedid J.A.; Caruso N.M.; Sana S.S.
This article deals with a mathematical model for multi-item inventory system under a collaborative scheme in a three-level supply chain consisting of multiple raw material suppliers, multiple manufacturers and multiple retailers in which different cycle lengths and stochastic demand and production rates are considered for the purpose of evaluating the optimal solution. The model is also validated in the supply chain of wood and furniture industry in the Caribbean region of Colombia. In the process, suppliers of raw wood (sawmills), manufacturers of home furnishings and major retailers are participated. Results include a comparison between three-level and two-level supply chains using the collaborative scheme as well as for the non-collaborative scheme among the participating members of the chain. © 2016, © 2016 Informa UK Limited, trading as Taylor & Francis Group.
Application of genetic algorithm to job scheduling under ergonomic constraints in manufacturing industry
(Springer Verlag, 2019) Sana S.S.; Ospina-Mateus H.; Arrieta F.G.; Chedid J.A.
This research proposes a mathematical model of the problem of job rotation considering ergonomic aspects in repetitive works, lifting tasks and awkward postures in manufacturing environments with high variability. The mathematical model is formulated as a multi-objective optimization problem integrating the ergonomic constraints and is solved using improved non-dominated sorting genetic algorithm. The proposed algorithm allows the generation of diversified results and a greater search convergence on the Pareto front. The algorithm avoids the loss of convergence in each border by means of change and replacement of similar solutions. In this strategy, a single similar result is preserved and the best solution of the previous generation is included. If the outcomes are similar, new randomly generated individuals are proposed to encourage diversity. The obtained results improve the conditions of 69% of the workers. The results show that if the worker rotates starting from a high risk, his variation in risk always decreases in his next assignment. Within the job rotation scheme, no worker is exposed simultaneously to high ergonomic risk thresholds. The model and the algorithm provide good results while considering ergonomic risks. The proposed algorithm shows the potentiality to generate a set of quality of response (Pareto Frontier) in a combinatorial optimization problem in an efficient computational time. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.