A New Approach for Solving Bi-Objective Redundancy Allocation Problem Using DOE, Simulation and &lt;italic&gt;ε&lt;/italic&gt;-Constraint Method

Ghorabaee, Mehdi Keshavarz; Amiri, Maghsoud; Turskis, Zenonas

doi:10.15388/informatica.2017.121

Cited by 3 publications

(2 citation statements)

References 44 publications

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“…Likewise, µ3 maximized in the objective function without considering µ1 and µ2. In literature, the lot-sizing problem has been referred to as an NP-hard problem as it deals with a significant number of variables (Keshavarz Ghorabaee et al, 2017). Therefore, to check the proposed algorithm's complexity, it is essential to conduct experiments with bigger sample size.…”

Section: Sensitivity Analysis By Changing µ1 µ2 and µ3 Individuallmentioning

confidence: 99%

Joint Multi-item Multi-supplier Sustainable Lot-sizing Model Applying Combined BWM, TOPSIS, Possibilistic Programming, and ε-constraint Method

Shaw

Lahri

Shankar

2021

Preprint

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Procurement decisions play a vital part in the sustainable transformation of the supply chain. Till now, a variety of supplier selection and lot-sizing models have been suggested, in particular, focusing on carbon emissions in a deterministic environment. It is noted that stressing only on carbon emissions cannot fully transform a sustainable supply chain. The present study argues that with carbon footprint, other dimensions, such as social sustainability, water footprint, recycled material use, solid and liquid waste, need to be considered in sustainable procurement decisions. To fill the gaps, this study proposed a three-stage multi-objective multi-supplier, multi-period joint supplier selection, and a lot-sizing model, taking into account carbon footprint, water footprint, solid and liquid waste, and use of recycled materials in a stochastic environment. The model optimizes three objectives (cost, carbon emission, and social sustainability). The model considers different model parameters as uncertain, such as costs, emission, solid waste, liquid waste, recycled material, quality rejection, and capacity. The present study suggests how to quantify social sustainability and further use it in the lot-sizing model. The proposed study has been carried out in three stages. In the first stage, BWM (Best-Worst method) and TOPSIS are applied to evaluate suppliers' social scores. In the second stage, the suppliers' social scores are used in the proposed possibilistic lot-sizing model. In the third stage, various trade-off curves are generated by applying the ε-constraint method. The model produces distinct optimal solutions for different uncertainty levels, which are used to create trade-off curves among the cost, emission, and social dimensions. The results facilitate decision-makers to decide the lot-size in an ambiguous environment.

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Section: Sensitivity Analysis By Changing µ1 µ2 and µ3 Individuallmentioning

confidence: 99%

Joint Multi-item Multi-supplier Sustainable Lot-sizing Model Applying Combined BWM, TOPSIS, Possibilistic Programming, and ε-constraint Method

Shaw

Lahri

Shankar

2021

Preprint

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“…To resolve this issue, a methodology is developed by Mavrotas and Florios [13] named as an augmented ε-constraint approach. Several authors applied this methodology to get an efficient solution in multi-objective optimization [14][15][16][17][18]. Du et.al.…”

Section: Literature Reviewmentioning

confidence: 99%

Integration of Triple Sustainable Management by Considering the Multi-period Supply Chain for Next-Generation Fuel

Ahmed¹,

Sarkar²,

Agha³

2020

IFIP Advances in Information and Communication Technology

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Energy sources depending on biofuel have a positive impact on the environment, economy, and society. To use this next-generation fuel appropriately at a developed scale, well-designed and efficient supply chain management are desired. Therefore, it is necessary to design and develop a sustainable biofuel supply chain that is economical, minimizes environmental threats, and improves social benefits. In this study, a multi-period multi-objective sustainable supply chain management is developed. This long-term planning horizon is divided into an equivalent number of sub-periods in which all objectives are executed simultaneously. The objective is to make a framework of the multiperiod sustainable supply chain management that reduces the carbon emission and take full advantage of the new job opportunities in the entire period. The parameters in this model are needed to extend during the time to meet the upward demand for markets. The augmented ε-constraint approach with an improved way of computing the step size is used to make a trade-off between contending objectives. The findings will help the organizations to respond accordingly for different parameters and regulations while designing the long-term planning for second-generation biofuel supply chain management.

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Joint Multi-item Multi-supplier Sustainable Lot-Sizing Model Applying Combined BWM, TOPSIS, Possibilistic Programming, and ϵ-constraint Method

Shaw

Lahri

Shankar

et al. 2024

IEEE Trans. Eng. Manage.

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A New Approach for Solving Bi-Objective Redundancy Allocation Problem Using DOE, Simulation and <italic>ε</italic>-Constraint Method

Cited by 3 publications

References 44 publications

Joint Multi-item Multi-supplier Sustainable Lot-sizing Model Applying Combined BWM, TOPSIS, Possibilistic Programming, and ε-constraint Method

Joint Multi-item Multi-supplier Sustainable Lot-sizing Model Applying Combined BWM, TOPSIS, Possibilistic Programming, and ε-constraint Method

Integration of Triple Sustainable Management by Considering the Multi-period Supply Chain for Next-Generation Fuel

Joint Multi-item Multi-supplier Sustainable Lot-Sizing Model Applying Combined BWM, TOPSIS, Possibilistic Programming, and ϵ-constraint Method

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