Centralized resource allocation with stochastic data

Lotfı, Farhad Hosseinzadeh; Nematollahi, Nader; Behzadi, Mohammad Hassan; Mirbolouki, Mahnaz; Moghaddas, Zohreh

doi:10.1016/j.cam.2011.10.009

Cited by 29 publications

(8 citation statements)

References 9 publications

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“…For example, Fang and Zhang (2008) allocated variable resources to DMUs by maximizing both the total efficiency from centralized decision-making environment and the individual efficiency for each DMU. Lotfi, Noora, Jahanshahloo, Gerami, and Mozaffari (2010) and Lotfi, Nematollahi, Behzadi, Mirbolouki, and Moghaddas (2012) addressed the centralized resource allocation problem using enhanced Russell models. Given a capital budget constraint, Lozano, Villa, and Canca (2011) proposed a series of centralized DEA models for individual and collective output target setting, input reallocation and additional input acquisitions.…”

Section: Dea-based Resource Allocation Studymentioning

confidence: 99%

Carbon emission abatement quota allocation in Chinese manufacturing industries: An integrated cooperative game data envelopment analysis approach

Emrouznejad

Yang

et al. 2019

Journal of the Operational Research Society

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The Chinese government announced to cut its carbon emissions intensity by 60%-65% from its 2005 level. To realize the national abatement commitment, a rational allocation into its subunits (i.e. industries, provinces) is eagerly needed. Centralized allocation models can maximize the overall interests, but might cause implementation difficulty and fierce resistance from individual subunits. Based on this observation, this article will address the carbon emission abatement quota allocation problem from decentralized perspective, taking the competitive and cooperative relationships simultaneously into account. To this end, this article develops an integrated cooperative game data envelopment analysis (DEA) approach. We first investigate the relative efficiency evaluation by taking flexible carbon emission abatement allocation plans into account, and then define a super-additive characteristic function for developing a cooperative game among units. To calculate the nucleolus-based allocation plan, a practical computation procedure is developed based on the constraint generation mechanism. Further, we present a two-layer way to allocate the CO 2 abatement quota into different sub-industries and further different provinces in Chinese manufacturing industries. The empirical results show that five sub-industries (Processing of petroleum, coking and processing of nuclear fuel; Smelting and pressing of ferrous metals; Manufacture of non-metallic mineral products; Manufacture of raw chemical materials and chemical product; Smelting and pressing of non-ferrous metals) and two provinces (Guangdong and Shandong) will be allocated more than 10% of the total national carbon emission abatement quota.

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Section: Dea-based Resource Allocation Studymentioning

confidence: 99%

Carbon emission abatement quota allocation in Chinese manufacturing industries: An integrated cooperative game data envelopment analysis approach

Emrouznejad

Yang

et al. 2019

Journal of the Operational Research Society

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“…Stochastic input and output variations of DEA have been studied by many researchers including: Land et al (1993), Olesen and Petersen (1995), Huang and Li (1996), Li (1998), Morita and Seiford (1999), Cooper et al (1996Cooper et al ( , 1998Cooper et al ( , 2002Cooper et al ( , 2004, Bruni et al (2009, Khodabakhshi and Asgharian (2009), Khodabakhshi (2009, 2010, Wu and Lee (2010), Khodabakhshi (2011) andHosseinzadeh Lotfi et al (2012). Land et al (1993) exploited the CCP proposed by Charnes and Cooper (1959) in order to compute efficiency in the face of uncertainty.…”

Section: Introductionmentioning

confidence: 99%

A new chance-constrained DEA model with birandom input and output data

Tavana

Shiraz

Hatami-Marbini

2014

Journal of the Operational Research Society

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The purpose of conventional Data Envelopment Analysis (DEA) is to evaluate the performance of a set of firms or Decision-Making Units using deterministic input and output data. However, the input and output data in the real-life performance evaluation problems are often stochastic. The stochastic input and output data in DEA can be represented with random variables. Several methods have been proposed to deal with the random input and output data in DEA. In this paper, we propose a new chance-constrained DEA model with birandom input and output data. A super-efficiency model with birandom constraints is formulated and a non-linear deterministic equivalent model is obtained to solve the super-efficiency model. The non-linear model is converted into a model with quadratic constraints to solve the non-linear deterministic model. Furthermore, a sensitivity analysis is performed to assess the robustness of the proposed super-efficiency model. Finally, two numerical examples are presented to demonstrate the applicability of the proposed chance-constrained DEA model and sensitivity analysis.

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“…Bain and Yang [7] developed several DEA models for measuring the aggregated efficiency of resource and environment based on environment DEA technology, which can be provided with an index to analyse DMU energy efficiencies and environmental efficiencies simultaneously. A centralized resource allocation (CRA) DEA method for accidental data, namely SCRA model, was suggested by Hosseinzadeh Lotfi et al *For correspondence [8]. Their approach creates a stochastic DEA structure for CRA.…”

Section: Introductionmentioning

confidence: 99%

A data envelopment analysis approach for resource allocation with undesirable outputs: an application to home appliance production companies

Nemati

Matin

2019

Sādhanā

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Traditional data envelopment analysis (DEA) models use all multiple inputs and outputs to estimate efficiency scores of decision-making units (DMUs). Each unit may consist of several subunits in cases such as manufacturing systems, and each subunit may produce both desirable and undesirable outputs. Providing information about the proportion of resources for each subunit could assist managers in making better decisions for increasing the efficiency of production systems. The current study proposes a new approach for resource allocation and efficiency estimation of production units by considering partial impacts among inputs and outputs in the DEA framework. A weak disposable technology is used in these evaluations, and an empirical application of the proposed approach for obtaining performance of home appliances production companies is provided for illustration purposes.

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Centralized resource allocation with stochastic data

Cited by 29 publications

References 9 publications

Carbon emission abatement quota allocation in Chinese manufacturing industries: An integrated cooperative game data envelopment analysis approach

Carbon emission abatement quota allocation in Chinese manufacturing industries: An integrated cooperative game data envelopment analysis approach

A new chance-constrained DEA model with birandom input and output data

A data envelopment analysis approach for resource allocation with undesirable outputs: an application to home appliance production companies

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