Designing a Mathematical Model for Sustainable Industrial Tourism Supply Chain Considering Responsiveness: A Case Study

Document Type : Original Article

Authors

1 Ph.D. Student, Department of Industrial Engineering, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.

2 Professor, Department of Industrial Engineering, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.

3 Associate Professor, Department of Industrial Engineering, Faculty of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran.

4 Professor, Department of Industrial Engineering, Faculty of Materials and Industrial Engineering, Babol Noshirvani University of Technology, Babol, Iran.

Abstract

Introduction and Objectives. In recent years, tourism development has played a very important role in the development of any society. Today, industrial tourism, as a branch of tourism, simultaneously benefits from the capabilities of both industry and tourism for the development of any society. A review of the literature on the subject shows that despite the importance of this field, it has not received significant attention in recent years. Therefore, to fill this research gap, the present study focuses on the aforementioned issue. Since the best way to develop any field is to examine its supply chain. Therefore, to achieve the research objective, the industrial tourism supply chain network has first been studied and designed. One of the important issues in the field of tourism is the issue of sustainability. To consider the issue in question and examine the proposed supply chain, a bi-objective mathematical model including maximizing the profit of the supply chain and maximizing the its level of responsiveness has been designed and presented.
Method. Given the nature of the mathematical model, which is a bi-objectives model, the Revised Multi Choice Goal Programming (RMCGP) method has been used to solve the desired problem. RMCGP method is an extension of the classical goal programming method designed to solve Multi-Objective Decision-Making (MADM) problems with flexible and multi-option goals. This method allows decision-makers to express their preferences in an interval or multi-option form and has greater flexibility in modeling real problems. In this method, instead of defining a single goal and trying to optimize it, several goals with different levels are defined and the goal of planning is to achieve the closest possible state to these goals.
Findings and discussion. The proposed bi-objectives mathematical model, which includes maximizing supply chain profit and maximizing the level of responsiveness in the proposed chain, has been solved using the RMCGP method based on data from a case study in Mazandaran province, Iran and the optimal value of the first Objective Function (OF) was 154,690,000 Tomans and the value of the second objective function was 0.6086. To solve the proposed model using the RMCGP method, the ideal and anti-ideal values ​​for the OF1 are 154,690,000 and zero respectively, and for OF2 are 0.6086 and zero respectively. Also, the importance degree of OF1 and OF2 are considered 0.6 and 0.4 respectively. The results of implementing the RMCGP method indicate that the value of OF1 does not change with the above assumptions and according to the proposed method, and OF2 is reduced to 0.3695.
Conclusion. In this research, industrial tourism has been studied by examining and designing its supply chain and presenting a mathematical model for the proposed supply chain for the first time. The proposed chain includes the customer group, the center providing industrial tourism services (facilitator), and industrial units and accommodation centers. The proposed model is a bi-objectives model including maximizing the chain profit and maximizing the level of responsiveness of the proposed chain. The proposed model has been solved using the RMCGP method and based on data from a case study in Mazandaran province,Iran. Considering the one-month planning horizon, the demand value and the the capacity limitations, the optimal value of the OF1 is 154,690,000 Tomans and OF2 is 0.6086. Also, to examine the proposed model more precisely, a sensitivity analysis is performed on some key parameters including the demand value of the facilitator center, the percentage of profit exchange between the facilitator center and industrial units, and the maximum allowable distance for allocating customer groups after visiting industrial units to accommodation centers, and its effects on changes in each OF have been examined.

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References

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Journal of Industrial Management Perspective
Volume 15, Issue 4 - Serial Number 60
December 2025
Pages 116-142

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