Green supply chain quantitative models for sustainable inventory management: A review

Becerra, Pablo; Mula, Josefa; Sanchís, Raquel

doi:10.1016/j.jclepro.2021.129544

Cited by 53 publications

(23 citation statements)

References 90 publications

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“…However, this section only provides an overview of the most relevant studies where integrated production and transportation scheduling in the supply chain networks has been addressed. Interested readers are referred to the review study by Becerra and Sanchis 7 and Emenike and Falcone 8 for a comprehensive overview of the green and energy‐efficient supply chain using optimization techniques.…”

Section: Literature Reviewmentioning

confidence: 99%

Energy‐efficient and sustainable supply chain in the manufacturing industry

Beheshtinia

Fathi

2022

Energy Science & Engineering

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This study aims at reducing energy consumption in supply chain networks by providing optimal integrated production and transportation scheduling. The considered supply chain consists of one main manufacturing center, multiple production units (i.e., suppliers), and multiple heterogeneous vehicles as the transportation fleet. To schedule this complex supply chain network in an energy-efficient way, several decisions should be made concerning the assignment of orders to suppliers and determining their production sequence, splitting orders, assigning orders to vehicles, and assigning delivery priority to orders. To cope with the problem, a mixed-integer linear programming model is presented. Due to the complexity of the problem, a novel development of the genetic algorithm named the Multiple Reference Group Genetic Algorithm (MRGGA) is also proposed. Four objectives are considered to be optimized to meet both suitability and energy-efficiency aspects in the supply chain network. These optimization objectives are to minimize the total orders' delivery times to the manufacturing center, fuel consumption by the vehicles, energy consumption at supplies, and maximize orders' quality. To analyze the performance of the proposed algorithm, a real case and a set of generated instances are solved. The results obtained by the proposed algorithm are compared with an existing genetic algorithm in the literature. Moreover, the results are also compared with the optimal solutions obtained from the mathematical model for small-size problems. The results of the comparisons show the efficiency of the proposed MRGGA in finding energy-efficient solutions for the considered supply chain network.

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Section: Literature Reviewmentioning

confidence: 99%

Energy‐efficient and sustainable supply chain in the manufacturing industry

Beheshtinia

Fathi

2022

Energy Science & Engineering

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“…The model was initially proposed by Goyal (1977) and GoyalDeshmukh (1992) Sustainability requires an integrated and collaborative approach in supply chain networks. It is also important to note that sustainable inventory management is one aspect of sustainable supply chain management (Becerra et al, 2021) which is critical and recognized as corporate social and environmental responsibility (Pattnaik et al, 2021). The previous studies that have been conducted on sustainable production inventory models are summarized in Table 1.…”

Section: Content Analysis and Gapsmentioning

confidence: 99%

Sustainable Production-Inventory Model with Multi-Material, Quality Degradation, and Probabilistic Demand: From Bibliometric Analysis to A Robust Model

Utama

Santoso

Hendrawan

et al. 2022

Indonesian J. Sci. Technol

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An adequate sustainable production inventory model is expected to represent complex real-life cases involving fuel, emissions, and electricity costs as well as multi-materials, quality degradation, and probabilistic demand. Therefore, this study was conducted to develop this kind of model to determine the number of raw material shipments (), production cycle time (), and the number of finished goods delivered (n) to maximize the Expected Total Profit (ETP). The proposed model is based on a bibliometric literature analysis of the sustainable production-inventory problem which is visualized using the VOSviewer. Moreover, a sophisticated Harris-Hawks Optimization (HHO) algorithm was proposed to solve the problems identified in the sustainable production inventory model optimization. It is also important to note that three numerical cases were provided to evaluate the performance of the algorithm. The findings showed that the suggested HHO method outperforms the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in maximizing ETP and this means it is better for ETP optimization. It was also discovered from the sensitivity analysis that an increase in the rate of quality degradation (k) led to a reduction in both the ETP and T.

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“…Consequently, the utilization of a proficient inventory framework can improve responsiveness and service delivery. Additionally, the optimization of the inventory storage framework should be accomplished to improve the functional effectiveness and rapid response to client requests (Becerra, Mula, & Sanchis, 2021 ;Anumala, 2021). This will lead to diminished inventory cost and maximise profits.…”

Section: Inventory Management Sustainabilitymentioning

confidence: 99%

Inventory Management Sustainability

Adedugba

Ogunnaike

Adeyemo

et al. 2022

International Journal of System Dynamics Applications

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Inventory optimality is an option of energy utilization proportionality that can lessen carbon emanations and maximize profitability. This study proposes an inventory management model in which the stock volume is optimally decided to diminish energy per resource utilized in-other to reduce carbon emanations. This will likewise help in concluding renewal volume optimally. Consequently, the study utilized economic order quantity (EOQ) to decide inventory volumes in-other to decrease carbon emanations so as to augment profits of the inventory chain. Partial least square(PLS) was additionally utilized to examine the extent of inventory management frameworks on environmental sustainability. The study, therefore, shows its oddity and pertinency by utilizing economic order quantity(EOQ) and partial least square(PLS) to examine and optimize inventory respectively, as it gives a perspective of decreasing carbon emanations during inventory procedures.

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Green supply chain quantitative models for sustainable inventory management: A review

Cited by 53 publications

References 90 publications

Energy‐efficient and sustainable supply chain in the manufacturing industry

Energy‐efficient and sustainable supply chain in the manufacturing industry

Sustainable Production-Inventory Model with Multi-Material, Quality Degradation, and Probabilistic Demand: From Bibliometric Analysis to A Robust Model

Inventory Management Sustainability

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