Inverse forecasting: A new approach for predictive modeling

Amin, Gholam R.; Emrouznejad, Ali

doi:10.1016/j.cie.2007.05.007

Cited by 9 publications

(6 citation statements)

References 15 publications

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“…Further research studies on inverse linear programming problems are given in Zhang and Liu (1999) and Huang and Liu (1999). One of the few applications of inverse linear programming in the literature is for predicting more accurate forecasting parameters developed in Amin and Emrouznejad (2007). The first inverse DEA methodology as a special case of the general inverse linear programming suggested in Wei et al (2000) and further developed in Yan et al (2002).…”

Section: Inverse Deamentioning

confidence: 99%

A novel inverse DEA model with application to allocate the CO₂ emissions quota to different regions in Chinese manufacturing industries

Emrouznejad

Yang

Amin

2018

Journal of the Operational Research Society

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This paper aims to address the problem of allocating the CO 2 emissions quota set by government goal in Chinese manufacturing industries to different Chinese regions. The CO 2 emission reduction is conducted in a three-stage phases. The first stage is to obtain the total amount CO 2 emission reduction from the Chinese government goal as our total CO 2 emission quota to reduce. The second stage is to allocate the reduction quota to different two-digit level manufacturing industries in China. The third stage is to further allocate the reduction quota for each industry into different provinces. A new inverse data envelopment analysis (InvDEA) model is developed to achieve our goal to allocate CO 2 emission quota under several assumptions. At last we obtain the empirical results based on the real data from Chinese manufacturing industries.

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Section: Inverse Deamentioning

confidence: 99%

A novel inverse DEA model with application to allocate the CO₂ emissions quota to different regions in Chinese manufacturing industries

Emrouznejad

Yang

Amin

2018

Journal of the Operational Research Society

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“…They developed an approach to realize the required level of the merged bank's inputs and outputs to reach a predetermined efficiency target. (Amin & Emrouznejad, 2007) applied the inverse optimization for forecasting and provided a streamlined approach to time series analysis using inverse linear programming. (Amin, Emrouznejad, & Gattoufi, 2017) proposed inverse DEA models for modeling generalized firms' restructuring and anticipating the minor and major consolidation for a merger in a market.…”

Section: Introductionmentioning

confidence: 99%

New inverse DEA models for budgeting and planning

2021

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Data envelopment analysis (DEA) measures the efficiency score of a set of homogeneous decision-making units (DMUs) based on observed input and output. Considering input-oriented, the inverse DEA models find the required input level for producing a given amount of production in the current efficiency level. This article proposes a new form of the inverse DEA model considering income (for planning) and budget (for finance and budgeting) constraints. In contrast with the classical inverse model, both input and output levels are variable in proposed models to meet income (or budget) constraints. Proposed models help decision-makers (DMs) to find the required value of each input and each output's income share to meet the income or budget constraint. We apply the proposed model in the efficiency analysis of 58 supermarkets belonging to the same chain. However, these methods are general and can be used in the budgeting and planning process of any production system, including business sectors and firms that provide services.

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“…Huang and Liu [12] investigated some applications of the inverse of linear programming. Some various applications of the inverse problem have been studied by Amin and Emrouznejad [13]. Inverse linear programming and inverse quadratic programming using perturbation methods was investigated by Zhang et al [14,15].…”

Section: Introductionmentioning

confidence: 99%

Stability of Solutions for Parametric Inverse Nonlinear Cost Transportation Problem

Mousa

Abo-Elnaga

2020

Mathematics

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This paper investigates the solution for an inverse of a parametric nonlinear transportation problem, in which, for a certain values of the parameters, the cost of the unit transportation in the basic problem are adapted as little as possible so that the specific feasible alternative become an optimal solution. In addition, a solution stability set of these parameters was investigated to keep the new optimal solution (feasible one) is unchanged. The idea of this study based on using a tuning parameters λ∈Rm in the function of the objective and input parameters υ∈Rl in the set of constraint. The inverse parametric nonlinear cost transportation problem P(λ,υ), where the tuning parameters λ∈Rm in the objective function are tuned (adapted) as less as possible so that the specific feasible solution x∘ has been became the optimal ones for a certain values of υ∈Rl, then, a solution stability set of the parameters was investigated to keep the new optimal solution x∘ unchanged. The proposed method consists of three phases. Firstly, based on the optimality conditions, the parameter λ∈Rm are tuned as less as possible so that the initial feasible solution x∘ has been became new optimal solution. Secondly, using input parameters υ∈Rl resulting problem is reformulated in parametric form P(υ). Finally, based on the stability notions, the availability domain of the input parameters was detected to keep its optimal solution unchanged. Finally, to clarify the effectiveness of the proposed algorithm not only for the inverse transportation problems but also, for the nonlinear programming problems; numerical examples treating the inverse nonlinear programming problem and the inverse transportation problem of minimizing the nonlinear cost functions are presented.

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Inverse forecasting: A new approach for predictive modeling

Cited by 9 publications

References 15 publications

A novel inverse DEA model with application to allocate the CO₂ emissions quota to different regions in Chinese manufacturing industries

A novel inverse DEA model with application to allocate the CO₂ emissions quota to different regions in Chinese manufacturing industries

New inverse DEA models for budgeting and planning

Stability of Solutions for Parametric Inverse Nonlinear Cost Transportation Problem

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Inverse forecasting: A new approach for predictive modeling

Cited by 9 publications

References 15 publications

A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries

A novel inverse DEA model with application to allocate the CO2 emissions quota to different regions in Chinese manufacturing industries

New inverse DEA models for budgeting and planning

Stability of Solutions for Parametric Inverse Nonlinear Cost Transportation Problem

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Product

Resources

About

A novel inverse DEA model with application to allocate the CO₂ emissions quota to different regions in Chinese manufacturing industries

A novel inverse DEA model with application to allocate the CO₂ emissions quota to different regions in Chinese manufacturing industries