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Fatemeh Mohajernia, Jafar Rahmani, Seyfollah Fazlollahigh Gomshi,
Volume 17, Issue 1 (5-2026)
Abstract
Extant quantitative models in Resource Allocation and Operational Systems often rely on statistical optimization or behavioral frameworks, frequently failing to model and quantify the deterministic structural conflicts that arise when operational and informational constraints are ignored. This paper addresses a critical analytical gap in Industrial Information Integration: the necessity of a deterministic modeling framework to quantify the systemic risks inherent in resource scarcity and misallocation. We introduce a novel analytical framework, derived from the Generalized Pigeonhole Principle (GPP), to quantify the inevitable consequences of resource imbalance within complex organizational systems. The framework develops a three-tiered conceptual model: (1) the Base Principle (quantifying the inevitable Structural Non-Allocation Rate, (N-M)), (2) the Generalized Principle (modeling Inevitable Operational Congestion, λ min), and (3) the Weighted Principle (quantifying Qualitative Mismatch, f). We demonstrate the model's predictive and explanatory power through scenario-based analytical simulations, providing a foundational validation for its applicability across workforce planning and capacity development contexts. The analysis yields testable propositions linking these mathematical inevitabilities directly to systemic consequences (e.g., structural attrition/turnover, intragroup operational conflict). This research provides a new, parsimonious analytical language for Operational Systems Modeling, fundamentally shifting the focus from optimizing individual performance to managing unavoidable structural pressures. The model serves as a robust quantitative decision-support tool for strategic workforce planning and lays the essential groundwork for future dynamic modeling of operational capacity and resource demand.
Dr Hassan Rostamzadeh, Dr Ali Reza Fakharzadeh,
Volume 17, Issue 1 (5-2026)
Abstract
Existing merger approaches in data envelopment analysis integrate decision-making units in a single stage, but in practice, merging units may not be possible or affordable at once. We propose a finite multi-stage framework for the gradual merger of decision-making units that incorporates practical constraints. The model determines input and output contributions of the merged units at each stage and constructs a strictly increasing efficiency sequence that converges to a Pareto-efficient state. Each new unit is optimized using both input and output orientation while preserving a uniform return to scale type across stages. The framework is validated through a multi-stage merger application on a subset of Iranian banks.
F. Ahmadi, S. Kordrostami, M. Mirzaei Chalakei, L. Khoshandam,
Volume 17, Issue 1 (5-2026)
Abstract
Measuring capacity utilization is an important aspect among processes in order to determine overcapacity or undercapacity. Furthermore, in many situations, the convexity and homogeneity properties are not satisfied. Accordingly, in this paper, meta-frontier free disposal hull (FDH) frameworks are proposed to estimate output-oriented and input-oriented capacity utilization (CU) rates of firms under nonconvexity property and heterogeneity of technology. Also, the introduced technique is applied to assess capacity utilization of some Iranian hospitals. The findings show the presented approach is beneficial to measure capacity utilization rates of systems in the presence of nonconvexity and heterogeneity.
Forouzesh Ghambari, Mahdi Ahangari,
Volume 17, Issue 2 (9-2026)
Abstract
Cooperative game theory is an important tool for analyzing cooperation and benefit allocation among coalition members, but classical models usually do not consider the existence of a minimum capacity required for cooperation to be activated. In this study, “threshold coalition games” are introduced, in which the formation of an effective coalition requires crossing a certain threshold of collective capacity. Also, a coalition activation index and a new rule called “threshold allocation value” are presented to determine the players’ shares, and their properties, including efficiency, symmetry, and uniqueness, are proven. Finally, a numerical example shows that the proposed model can model threshold-based cooperation structures coherently and provides a suitable framework for future research in cooperative game theory.
Dr Amir-Mohammad Golmohammadi, Naser Ghorbani, Dr Fateme Rashidian,
Volume 17, Issue 2 (9-2026)
Abstract
The optimal planning of hybrid renewable energy systems has become increasingly important due to rising energy demand, environmental concerns, and the need for reliable electricity supply in remote and isolated regions. This study presents a comprehensive mixed-integer linear programming (MILP) framework for the optimal design of a hybrid solar–wind–battery–fuel cell–diesel microgrid. The proposed model simultaneously determines the optimal type, size, and operation of system components over the project lifetime while minimizing the equivalent annual cost. Unlike many existing optimization approaches, the framework integrates economic, environmental, and reliability considerations into a unified objective function by incorporating carbon emission penalties, load curtailment penalties, and renewable energy incentive policies. Furthermore, replacement costs and component lifetime degradation are reformulated into linear constraints, enabling the problem to be solved efficiently using exact optimization techniques. Hourly meteorological and load data are employed to accurately capture seasonal and daily variations in renewable energy generation and electricity demand. The optimization model is implemented in GAMS and solved using the CPLEX solver. Different system configurations and regulatory scenarios are evaluated to investigate the influence of diesel generators, battery storage, hydrogen technologies, and government support policies on system performance. The results demonstrate that an appropriately designed hybrid microgrid can substantially improve renewable energy penetration while maintaining system reliability and reducing the overall lifecycle cost. Moreover, regulatory incentive mechanisms significantly increase the economic viability of renewable energy resources and decrease dependence on fossil-fuel-based generation. The proposed MILP framework provides an effective decision-support tool for policymakers, system planners, and investors involved in the development of sustainable hybrid microgrids.
Seyyed Mehdi Hosseini, Mohammad Saidi-Mehrabad, Rouzbeh Ghousi, Ahmad Makoui, Mohammad Mahdi Paydar,
Volume 17, Issue 2 (9-2026)
Abstract
Industrial Tourism (IT) can lead to economic prosperity, job creation, capital attraction, and greater interaction between industry and society. On the other hand, the Industrial Tourism Supply Chain (ITSC) comprises activities and stakeholders, including transportation, industrial units, accommodation centers, and facilitators, whose coordinated performance directly affects the quality of tourists' experience and the efficiency of this industry. Therefore, the present study examines ITSC considering sustainability aspects to address gaps in the field. Moreover, the important issue of destination attractiveness is considered in the proposed model. The proposed model is solved using the Revised Multiple-Choice Goal Program (RMCGP) method. To evaluate the proposed model, a case study in Mazandaran province, Iran, is considered, and a sensitivity analysis is conducted on some key parameters. The output results show that the activity in this industry and the provision of services are economically justified.
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