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Article
Publication date: 28 June 2022

Peter Wanke, Sahar Ostovan, Mohammad Reza Mozaffari, Javad Gerami and Yong Tan

This paper aims to present two-stage network models in the presence of stochastic ratio data.

Abstract

Purpose

This paper aims to present two-stage network models in the presence of stochastic ratio data.

Design/methodology/approach

Black-box, free-link and fix-link techniques are used to apply the internal relations of the two-stage network. A deterministic linear programming model is derived from a stochastic two-stage network data envelopment analysis (DEA) model by assuming that some basic stochastic elements are related to the inputs, outputs and intermediate products. The linkages between the overall process and the two subprocesses are proposed. The authors obtain the relation between the efficiency scores obtained from the stochastic two stage network DEA-ratio considering three different strategies involving black box, free-link and fix-link. The authors applied their proposed approach to 11 airlines in Iran.

Findings

In most of the scenarios, when alpha in particular takes any value between 0.1 and 0.4, three models from Charnes, Cooper, and Rhodes (1978), free-link and fix-link generate similar efficiency scores for the decision-making units (DMUs), While a relatively higher degree of variations in efficiency scores among the DMUs is generated when the alpha takes the value of 0.5. Comparing the results when the alpha takes the value of 0.1–0.4, the DMUs have the same ranking in terms of their efficiency scores.

Originality/value

The authors innovatively propose a deterministic linear programming model, and to the best of the authors’ knowledge, for the first time, the internal relationships of a two-stage network are analyzed by different techniques. The comparison of the results would be able to provide insights from both the policy perspective as well as the methodological perspective.

Details

Journal of Modelling in Management, vol. 18 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

Article
Publication date: 6 August 2020

Mohammad Tavassoli, Amirali Fathi and Reza Farzipoor Saen

The purpose of this study is to propose a novel super-efficiency DEA model to appraise the relative efficiency of DMUs with zero data and stochastic data. Our model can work with…

Abstract

Purpose

The purpose of this study is to propose a novel super-efficiency DEA model to appraise the relative efficiency of DMUs with zero data and stochastic data. Our model can work with both variable returns to scale (VRS) and constant returns to scale (CRS).

Design/methodology/approach

This study proposes a new stochastic super-efficiency DEA (SSDEA) model to assess the performance of airlines with stochastic and zero inputs and outputs.

Findings

This paper proposes a new analysis and contribution to the knowledge of efficiency assessment with stochastic super-efficiency DEA model by (1) using input saving and output surplus index for efficient DMUs to get the optimal solution; (2) obtaining efficiency scores from the proposed model that are equivalent to original stochastic super-efficiency model when feasible solutions exist. A case study is given to illustrate the applicability of our proposed model. Also, poor performance reasons are identified to improve the performance of inefficient airlines.

Originality/value

For the first time, a new SSDEA model for ranking DMUs is proposed. The introduced model produces a feasible solution when dealing with zero input or output. This paper applies the input saving and output surplus concept to rectify the infeasibility problem in the stochastic DEA model.

Details

Benchmarking: An International Journal, vol. 28 no. 1
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 6 June 2019

Nabil M. Semaan and Nabhan Yehia

The purpose of this paper is to develop a stochastic detailed schedule for a preventive/scheduled/periodic maintenance program of a military aircraft, specifically a rotorcraft or…

Abstract

Purpose

The purpose of this paper is to develop a stochastic detailed schedule for a preventive/scheduled/periodic maintenance program of a military aircraft, specifically a rotorcraft or helicopter.

Design/methodology/approach

The new model, entitled the military “periodic aviation maintenance stochastic schedule” (PAM-SS), develops a stochastic detailed schedule for a PUMA SA 330SM helicopter for the 50-h periodic inspection, using cyclic operation network (CYCLONE) and Monte Carlo simulation (MCS) techniques. The PAM-SS model identifies the different periodic inspection tasks of the maintenance schedule, allocates the resources required for each task, evaluates a stochastic duration of each inspection task, evaluates the probability of occurrence for each breakdown or repair, develops the CYCLONE model of the stochastic schedule and simulates the model using MCS.

Findings

The 50-h maintenance stochastic duration follows a normal probability distribution and has a mean value of 323 min and a standard deviation of 23.7 min. Also, the stochastic maintenance schedule lies between 299 and 306 min for a 99 per cent confidence level. Furthermore, except the pilot and the electrical team (approximately 90 per cent idle), all other teams are around 40 per cent idle. A sensitivity analysis is also performed and yielded that the PAM-SS model is not sensitive to the number of technicians in each team; however, it is highly sensitive to the probability of occurrence of the breakdowns/repairs.

Practical implications

The PAM-SS model is specifically developed for military rotorcrafts, to manage the different resources involved in the detailed planning and scheduling of the periodic/scheduled maintenance, mainly the 50-h inspection. It evaluates the resources utilization (idleness and queue), the stochastic maintenance duration and identifies backlogs and bottlenecks.

Originality/value

The PAM-SS tackles military aircraft planning and scheduling in a stochastic methodology, considering uncertainties in all inspection task durations and breakdown or repair durations. The PAM-SS, although developed for rotorcrafts can be further developed for any other type of military aircraft or any other scheduled maintenance program interval.

Details

Aircraft Engineering and Aerospace Technology, vol. 91 no. 9
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 9 August 2021

Anwar Zeb, Sunil Kumar, Almaz Tesfay and Anil Kumar

The purpose of this paper is to investigate the effects of irregular unsettling on the smoking model in form of the stochastic model as in the deterministic model these effects…

Abstract

Purpose

The purpose of this paper is to investigate the effects of irregular unsettling on the smoking model in form of the stochastic model as in the deterministic model these effects are neglected for simplicity.

Design/methodology/approach

In this research, the authors investigate a stochastic smoking system in which the contact rate is perturbed by Lévy noise to control the trend of smoking. First, present the formulation of the stochastic model and study the dynamics of the deterministic model. Then the global positive solution of the stochastic system is discussed. Further, extinction and the persistence of the proposed system are presented on the base of the reproductive number.

Findings

The authors discuss the dynamics of the deterministic smoking model form and further present the existence and uniqueness of non-negative global solutions for the stochastic system. Some previous study’s mentioned in the Introduction can be improved with the help of obtaining results, graphically present in this manuscript. In this regard, the authors present the sufficient conditions for the extinction of smoking for reproductive number is less than 1.

Research limitations/implications

In this work, the authors investigated the dynamic stochastic smoking model with non-Gaussian noise. The authors discussed the dynamics of the deterministic smoking model form and further showed for the stochastic system the existence and uniqueness of the non-negative global solution. Some previous study’s mentioned in the Introduction can be improved with the help of obtained results, clearly shown graphically in this manuscript. In this regard, the authors presented the sufficient conditions for the extinction of smoking, if <1, which can help in the control of smoking. Motivated from this research soon, the authors will extent the results to propose new mathematical models for the smoking epidemic in the form of fractional stochastic modeling. Especially, will investigate the effective strategies for control smoking throughout the world.

Originality/value

This study is helpful in the control of smoking throughout the world.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. 32 no. 3
Type: Research Article
ISSN: 0961-5539

Keywords

Article
Publication date: 24 January 2020

Rita Shakouri, Maziar Salahi and Sohrab Kordrostami

The purpose of this paper is to present a stochastic p-robust data envelopment analysis (DEA) model for decision-making units (DMUs) efficiency estimation under uncertainty. The…

Abstract

Purpose

The purpose of this paper is to present a stochastic p-robust data envelopment analysis (DEA) model for decision-making units (DMUs) efficiency estimation under uncertainty. The main contribution of this paper consists of the development of a more robust system for the estimation of efficiency in situations of inputs uncertainty. The proposed model is used for the efficiency measurement of a commercial Iranian bank.

Design/methodology/approach

This paper has been arranged to launch along the following steps: the classical Charnes, Cooper, and Rhodes (CCR) DEA model was briefly reviewed. After that, the p-robust DEA model is introduced and then calculated the priority weights of each scenario for CCR DEA output oriented method. To compute the priority weights of criteria in discrete scenarios, the analytical hierarchy analysis process (AHP) is used. To tackle the uncertainty of experts’ opinion, a synthetic technique is applied based on both robust and stochastic optimizations. In the sequel, stochastic p-robust models are proposed for the estimation of efficiency, with particular attention being paid to DEA models.

Findings

The proposed method provides a more encompassing measure of efficiency in the presence of synthetic uncertainty approach. According to the results, the expected score, relative regret score and stochastic P-robust score for DMUs are obtained. The applicability of the extended model is illustrated in the context of the analysis of an Iranian commercial bank performance. Also, it is shown that the stochastic p-robust DEA model is a proper generalization of traditional DEA and gained a desired robustness level. In fact, the maximum possible efficiency score of a DMU with overall permissible uncertainties is obtained, and the minimal amount of uncertainty level under the stochastic p-robustness measure that is required to achieve this efficiency score. Finally, by an example, it is shown that the objective values of the input and output models are not inverse of each other as in classical DEA models.

Originality/value

This research showed that the enormous decrease in maximum possible regret makes only a small addition in the expected efficiency. In other words, improvements in regret can somewhat affect the expected efficiency. The superior issue this kind of modeling is to permit a harmful effect to the objective to better hedge against the uncertain cases that are commonly ignored.

Details

Journal of Modelling in Management, vol. 15 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

Content available

Abstract

Details

Kybernetes, vol. 41 no. 7/8
Type: Research Article
ISSN: 0368-492X

Article
Publication date: 1 February 2003

DIMITRIS PSYCHOYIOS, GEORGE SKIADOPOULOS and PANAYOTIS ALEXAKIS

The volatility of a financial asset is an important input for financial decision‐making in the context of asset allocation, option pricing, and risk management. The authors…

Abstract

The volatility of a financial asset is an important input for financial decision‐making in the context of asset allocation, option pricing, and risk management. The authors compare and contrast four approaches to stochastic volatility to determine which is most appropriate to each of these various needs.

Details

The Journal of Risk Finance, vol. 4 no. 3
Type: Research Article
ISSN: 1526-5943

Article
Publication date: 1 June 1998

A.S. Humphrey, G.D. Taylor and T.L. Landers

In this article, we present the results of a study examining the behavior of various inventory stocking methodologies in repair/rework operations. A major area of focus is on the…

1487

Abstract

In this article, we present the results of a study examining the behavior of various inventory stocking methodologies in repair/rework operations. A major area of focus is on the sensitivity of key model parameters to stochastic replenishment lead times, product demand, and overhaul factors. A case study in a US Army depot provides validation for the effort. Simulation results indicate the current depot stocking methodologies are adequate in ideal conditions, but are less effective in more challenging and realistic scenarios. Results also indicate that some commonly used inventory models are quite robust to stochastic operating parameters in the unique/rework environment.

Details

International Journal of Operations & Production Management, vol. 18 no. 6
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 2 August 2013

Andreas Pfnür and Stefan Armonat

The purpose of this paper is to apply a numerical simulation of stochastic processes to the problem of real estate investment appraisal.

1555

Abstract

Purpose

The purpose of this paper is to apply a numerical simulation of stochastic processes to the problem of real estate investment appraisal.

Design/methodology/approach

These uncertain operating costs are integrated into an enhanced dynamic simulation. To model the dynamics in the uncertainty of the cost schedule, a range of different types of stochastic processes is used. The operating costs are classified by cost drivers and an appropriate stochastic process is determined for each of the derived cost clusters. To optimise the capital structure in this application, heuristic optimisation with genetic algorithms is used.

Findings

The application of the model to real world investment situations shows that linear and deterministic modelling underestimates the risk‐generating effect of uncertain operating expenses, which often can lead to inefficient investment decisions.

Practical implications

In a further application of the model, the authors demonstrate the effect of uncertain operating costs on the optimal capital structure of real estate investments.

Originality/value

In contrast to models in the literature that are usually focussed on the income side, here the focus is on the uncertain dynamics of real estate operating costs as a key factor affecting return.

Article
Publication date: 9 April 2018

Harpreet Kaur and Surya Prakash Singh

Procurement planning has always been a huge and challenging activity for business firms, especially in manufacturing. With government legislations about global concern over carbon…

Abstract

Purpose

Procurement planning has always been a huge and challenging activity for business firms, especially in manufacturing. With government legislations about global concern over carbon emissions, the manufacturing firms are enforced to regulate and reduce the emissions caused throughout the supply chain. It is observed that procurement and logistics activities in manufacturing firms contribute heavily toward carbon emissions. Moreover, highly dynamic and uncertain business environment with uncertainty in parameters such as demand, supplier and carrier capacity adds to the complexity in procurement planning. The paper aims to discuss these issues.

Design/methodology/approach

This paper is a novel attempt to model environmentally sustainable stochastic procurement (ESSP) problem as a mixed-integer non-linear program. The ESSP optimizes the procurement plan of the firm including lot-sizing, supplier and carrier selection by addressing uncertainty and environmental sustainability. The model applies chance-constrained-based approach to address the uncertain parameters.

Findings

The proposed ESSP model is solved optimally for 30 data sets to validate the proposed ESSP and is further demonstrated using three illustrations solved optimally in LINGO 10.

Originality/value

The ESSP model simultaneously minimizes total procurement cost and carbon emissions over the entire planning horizon considering uncertain demand, supplier and carrier capacity.

Details

Management of Environmental Quality: An International Journal, vol. 29 no. 3
Type: Research Article
ISSN: 1477-7835

Keywords

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