Scenario-based designing of closed-loop supply chain with uncertainty in returned products

Cebeci

Ghorbani

et al. 2021

Logistics

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Backgroung: Lean innovation focuses on minimizing waste in the product development stages in order to increase productivity by obtaining customer feedback more quickly and efficiently. The usage of lean innovation practices in product development stages in the pharmaceutical supply chain is the topic of an increasing amount of research on the critical question of how lean innovation practices can be implemented in a pharmaceutical supply chain or logistic sector. To answer this question, we first identified lean innovation practices by reviewing the literature. Methods: the identified practices were screened using the fuzzy Delphi method (FDM). The expert panel included eight persons working in pharmaceutical supply chain fields. In the next step, the causal relationships between practices were analyzed using the Gray DEMATEL (GDEMATEL) technique. Results: show that technological knowledge was the most crucial factor in lean innovation practices in the pharmaceutical supply chain. Conclusions: Actualizing lean innovation in the supply chain is more than just utilizing the correct strategies and instruments. To execute lean innovation effectively, a reevaluation must be accomplished: A culture that recognizes requirements for change and is set up for consistent change is essential. Methodological strategies such as the value system cannot be set up as a one-time strategy. To execute lean innovation on a long-haul premise, members must be included and become acclimated to a proceeding with the progress process. Changes in forms are frequently used because of an absence of association of suppliers, regardless of whether measures are sensible.

Section: The Fuzzy Delphi Methodsmentioning

confidence: 99%

An Integrated Approach for Evaluating Lean Innovation Practices in the Pharmaceutical Supply Chain

Cebeci

Ghorbani

et al. 2021

Logistics

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“…Constraint (10) show that the value of the goods from the retailer to the consumer is equal to the market demand. Constraint (11) shows that a maximum of each selected supplier at any one time.…”

Section: Objective Functionsmentioning

confidence: 99%

“…Hence, market demand is stochastic and greatly depends on these two factors. Given the variable transport time and the level of product freshness, the decisions of the three parties involved in this supply chain are very complex and may lead to losses in cases of improper performance [11].…”

Section: Introductionmentioning

confidence: 99%

The Design of a Multi-Period and Multi-Echelon Perishable Goods Supply Network under Uncertainty

Yıldırım

Ghorbani

et al. 2022

Sustainability

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The value of superior supply network design is becoming increasingly important, especially in the perishable supply chain. Due to the recent developments in perishable products, perishable product supply chain (PPSC) management has attracted many researchers. The purpose of this study was to present a multi-period and multi-echelon perishable supply chain with regards to procurement time, cycle cost, and customer satisfaction. This study presented a new form of location-routing in a supply chain network for perishable products, accounting for environmental considerations, cost, procurement time, and customer satisfaction, such that the total costs, delivery time, and the emission of pollutants in the network were minimized while customer satisfaction was maximized. We formulated the problem as a multi-objective, nonlinear, mixed-integer program and the hybrid approach was proposed to solve the model. The mean error of the proposed algorithm for the objective function compared to the exact method in solving the sample problems was less than 3.4%. The computational results revealed the efficiency of the proposed algorithm for a wide range of issues of various sizes.

“…The problem studied in this article was used to provide a model for the optimal sequence of trucks and the cost of operations within the supply chain concerning three objectives (minimizing the cost of transportation, minimizing the sequence of transporting trucks, and minimizing carbon dioxide emissions) [42][43][44][45]. The mathematical model approach is complicated due to the high number of variables and limitations related to the number of trucks sending and receiving and the number of products required to solve the problem.…”

Section: Conclusion and Suggestionsmentioning

confidence: 99%

Optimizing Multi Cross-Docking Systems with a Multi-Objective Green Location Routing Problem Considering Carbon Emission and Energy Consumption

Sütütemiz

Yıldırım

et al. 2022

Energies

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Cross-docking is an excellent way to reduce the space required to store goods, inventory management costs, and customer order delivery time. This paper focuses on cost optimization, scheduling incoming and outgoing trucks, and green supply chains with multiple cross-docking. The three objectives are minimizing total operating costs, truck transportation sequences, and carbon emissions within the supply chain. Since the linear programming model is an integer of zero and one and belongs to NP-hard problems, its solution time increases sharply with increasing dimensions. Therefore, the non-dominated sorting genetic algorithm-II (NSGA-II) and the multi-objective particle swarm optimization (MOPSO) were used to find near-optimal solutions to the problem. Then, these algorithms were compared with criteria such as execution time and distance from the ideal point, and the superior algorithm in each criterion was identified.