Assessment of third-party logistics providers by introducing a new stochastic two-phase compromise solution model with last aggregation

Mohammadkhani, Atieh; Mousavi, Seyed Meysam

doi:10.1016/j.cie.2022.108324

Cited by 9 publications

(6 citation statements)

References 87 publications

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“…Efficiently handling product returns enhances resource utilization rates and contributes to the establishment of sustainable business operations (Mohammadkhani & Mousavi, 2022). However, products that have been returned may vary in terms of their conditions and quantities (Thibbotuwawa et al, 2023).…”

Section: Stockmentioning

confidence: 99%

“…However, products that have been returned may vary in terms of their conditions and quantities (Thibbotuwawa et al, 2023). Thus, an effective deployment of RL necessitates a well-suited logistics network (Mohammadkhani & Mousavi, 2022). The RL network of companies must have diverse options to handle these varying scenarios (Thibbotuwawa et al, 2023).…”

Section: Stockmentioning

confidence: 99%

“…Nevertheless, uncertainties stemming from diverse factors within the supply chain frequently influence the choice of implementing RL. A genuine RL functions within a dynamic environment of uncertainty (Mohammadkhani & Mousavi, 2022). Due to the unpredictable nature of demand, the irregular timing, and the varying quality of returned products, the need for flexible capacity and transportation services becomes imperative.…”

Section: Stockmentioning

confidence: 99%

“…Therefore, firms must develop appropriate strategies for overseeing the RL network and ensuring an optimal management process (Haq et al, 2023). Firms can choose from three alternatives to implement an effective RL network: handle it internally, establish logistics subsidiaries, or delegate RL activities to third-party partners, allowing them to focus on their core operations (Mohammadkhani & Mousavi, 2022). Today, most companies delegate their logistics activities to third-party providers (3PLs).…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Assessment of Third-Party Reverse Logistics Provider Through the SWARA-WASPAS Integrated Framework

Gürler

2024

Kahramanmaraş Sütçü İmam Üniversitesi Sosyal Bilimler Dergisi

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The selection of the most suitable third-party provider for reverse logistics (RL) activities is a key factor in initiating effective RL processes. However, the process of identifying the optimal third-party provider involves navigating through various conflicting objectives and criteria. This task is intricate and time-consuming, necessitating the application of multi-criteria decision-making (MCDM) approaches. This study addresses the evaluation and selection of the best 3PRLP by introducing a comprehensive MCDM framework. Therefore, this study aims to assist a manufacturer specializing in milk and dairy products who has opted to transfer its reverse logistics operations to a logistics service provider. The objective is to aid them in selecting the most suitable 3PRLP. The proposed framework incorporates the SWARA (Step-wise Weight Assessment Ratio Analysis) technique for determining weights and the WASPAS (Weighted Aggregated Sum Product Assessment) method for thoroughly evaluating alternatives. In this study, a panel of four experts made a joint decision after identifying six criteria and five alternatives. The research concluded that the reverse logistics cost (C1) emerges as the most pivotal factor, with the service quality of reverse logistics (C3) being recognized as the least significant criterion. As a result, A1 stands out as the top choice among the 3PRLP.

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Section: Stockmentioning

confidence: 99%

Section: Stockmentioning

confidence: 99%

Section: Stockmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessment of Third-Party Reverse Logistics Provider Through the SWARA-WASPAS Integrated Framework

Gürler

2024

Kahramanmaraş Sütçü İmam Üniversitesi Sosyal Bilimler Dergisi

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“…Imprecise information can be handled in various ways. Among them, probability and fuzzy sets (FSs) theories are popular approaches to address incomplete information [42][43][44][45]. In this respect, the robust possibilistic programming approach [40] was utilized to decrease the variation of parameters in the biofuel supply chain environment.…”

Section: Solution Approachmentioning

confidence: 99%

A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

et al. 2022

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In recent years, concerns regarding issues such as climate change, greenhouse gas emissions, fossil reserve dependency, and petroleum price fluctuation have led countries to focus on renewable energies. Meanwhile, in developing countries, designing an appropriate biofuel supply chain network regarding environmental competencies is an important problem. This paper presents a new bi-objective mixed integer mathematical model aiming to minimize CO2 emission and total costs in the process of the biofuel supply chain, creating a suitable green supply chain network. In this respect, CO2 emission and biofuel demand are regarded as uncertain data to address the real complex cases. Moreover, the SAUGMECON approach was implemented to construct a single objective model, and the obtained Pareto optimal points were depicted and analyzed. Thereby, a robust possibilistic programming approach was implemented to the proposed model to handle existing imprecise data. Furthermore, the applicability and performance of the proposed model were demonstrated based on an experimental example. In this respect, the obtained results from the proposed robust possibilistic programming model were compared with its crisp form to show the robustness and reliability of the proposed uncertain mathematical model.

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New XAI tools for selecting suitable 3D printing facilities in ubiquitous manufacturing

Wang

Chen

2023

Complex Intell. Syst.

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Several artificial intelligence (AI) technologies have been applied to assist in the selection of suitable three-dimensional (3D) printing facilities in ubiquitous manufacturing (UM). However, AI applications in this field may not be easily understood or communicated with, especially for decision-makers without relevant background knowledge, hindering the widespread acceptance of such applications. Explainable AI (XAI) has been proposed to address this problem. This study first reviews existing XAI techniques to explain AI applications in selecting suitable 3D printing facilities in UM. This study addresses the deficiencies of existing XAI applications by proposing four new XAI techniques: (1) a gradient bar chart with baseline, (2) a group gradient bar chart, (3) a manually adjustable gradient bar chart, and (4) a bidirectional scatterplot. The proposed methodology was applied to a case in the literature to demonstrate its effectiveness. The bidirectional scatterplot results from the experiment demonstrated the suitability of the 3D printing facilities in terms of their proximity. Furthermore, manually adjustable gradient bars increased the effectiveness of the AI application by decision-makers subjectively adjusting the derived weights. Furthermore, only the proposed methodology fulfilled most requirements for an effective XAI tool in this AI application.

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Assessment of third-party logistics providers by introducing a new stochastic two-phase compromise solution model with last aggregation

Cited by 9 publications

References 87 publications

Assessment of Third-Party Reverse Logistics Provider Through the SWARA-WASPAS Integrated Framework

Assessment of Third-Party Reverse Logistics Provider Through the SWARA-WASPAS Integrated Framework

A Robust Possibilistic Bi-Objective Mixed Integer Model for Green Biofuel Supply Chain Design under Uncertain Conditions

New XAI tools for selecting suitable 3D printing facilities in ubiquitous manufacturing

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