Efficiency status of a feasible solution in the Multi-Objective Integer Linear Programming problems: A DEA methodology

Keshavarz, Esmaeil; Toloo, Mehdi

doi:10.1016/j.apm.2014.11.032

Cited by 19 publications

(9 citation statements)

References 13 publications

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“…The principle of the DEA method is mainly to determine the relatively effective production frontier by means of Operations Research and Mathematical Statistics through the inputs and outputs of the DMUs that do not change and to evaluate the degree of deviation of each DMU from the DEA frontier [9]. BCC-DEA models can deal with variable returns to scale(BCC, also known as VRS) [10], which is frequently used in the analysis of port logistics efficiency where returns to scale are not constant. Through DEAP2.0 software, the technical efficiency of each port can be decomposed into scale efficiency and pure technical efficiency, which can further explore the bottlenecks restricting the improvement of technical efficiency and propose optional improvement plans.…”

Section: Dea Modelmentioning

confidence: 99%

Research on Logistics Efficiency of Chinese Ports above Designated Size Based on DEA-Malmquist Index

Huang¹

2022

Proceedings of the 2022 2nd International Conference on Enterprise Management and Economic Development (ICEMED 2022)

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The port is no longer a docking point for ships, but a multi-functional platform for sorting, warehousing, transportation and distribution due to the wide application of e-commerce logistics platforms. The continuous functioning and the efficiency have to be paid large attention to, which can promote faster exotic product delivery and lasting international commercial relationships. In order to measure the logistics efficiency of the port and identify defections, this paper selects provinces and cities where 11 important ports are located in China by the utilization of DEA-Malmquist index. The results show that the bottleneck of the growth rate of my country's port throughput appears. Taking the Qinling and Huaihe River as the boundary, the port transportation efficiency in the north is generally not as efficient as that in the south and even has a tendency to retreat. The improvement of port logistics efficiency should focus on increasing scale efficiency, improving resource allocation and management capabilities, finding new revenue growth points and reducing costs to break through bottlenecks.

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Section: Dea Modelmentioning

confidence: 99%

Research on Logistics Efficiency of Chinese Ports above Designated Size Based on DEA-Malmquist Index

Huang¹

2022

Proceedings of the 2022 2nd International Conference on Enterprise Management and Economic Development (ICEMED 2022)

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“…In the literature, several versions of the ε-constraint method have appeared trying to improve its performance or adapt it to a specific type of problems like MOIP problems (Keshavarz and Toloo, 2015;Mazidi et al, 2016). The technical novelties of the AUGMECON 2 method are: (a) construction of the payoff matrix in order to calculate the ranges of every objective functions; (b) avoidance of weakly Pareto optimal solutions by transforming the objective function constraints to equalities, by explicitly incorporating the appropriate slack (for minimisation objectives) or surplus (for maximisation objectives) variables; (c) early exit from the loops in order to treat the case of infeasibilities; and (d) less computational time (Xidonas et al, 2016b).…”

Section: Pareto Optimal Frontmentioning

confidence: 99%

Identifying optimal technological portfolios for European power generation towards climate change mitigation: A robust portfolio analysis approach

et al. 2019

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In this paper, an integrative approach is proposed to link integrated assessment modelling results with a novel portfolio analysis framework for robust modelling. The approach is applied for identifying optimal technological portfolios for power generation in the EU towards climate change mitigation, in a timescale until 2050. The technologies considered include photovoltaics, concentrated solar power, wind, nuclear, biomass and carbon capture and storage. The proposed approach links data from the Global Change Assessment Model (GCAM), namely subsidy curves for emissions reduction and energy security for the six power generation technologies until 2050, with other decision support methods, in the aim of managing the inherent uncertainty and assessing the robustness of the optimal portfolios. The modelling results are then integrated in a bi-objective evaluation model for portfolio analysis. The model treats uncertainty stochastically, using a Monte Carlo simulation algorithm and the Iterative Trichotomic Approach, and defines specific portfolios of electricity generation technologies as the most robust. The results are presented and discussed, mainly in terms of highlighting the robustness of the Pareto optimal solutions, which is essential for policymakers to be more confident when selecting technology portfolios that feature a high degree of uncertainty, regarding their vulnerability to different future developments. By aggregating the results to one robust technological portfolio, the proposed approach features the potential to subsequently be linked to a deterministic model.

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“…Belton and Stewart (2002) found that DEA emphasises on evaluating DMUs and finding targets to improve efficiency while MCDA focuses on ranking based on a set of criteria that include subjective judgment. Liu et al (2000), and Keshavarz and Toloo (2015) used DEA technique to obtain the efficiency status of a feasible solution in MOLP. Also, Hosseinzadeh-Lotfi et al (2010), Ebrahimnejad and Hosseinzadeh-Lotfi (2012), Yang et al (2009) as well as Yang and Xu (2014) found an equivalence relationship between the envelopment CCR model, proposed by Charnes et al (1978), and the weighted min-max MOLP formulation.…”

Section: Introductionmentioning

confidence: 99%

Characterisations of the production possibility set in data envelopment analysis: an MOLP approach

Mirdehghan

Heydari

2018

IJMOR

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The production possibility set in data envelopment analysis is a polyhedron and it is defined by the intersection of a finite number of half spaces which are constructed by their corresponding defining hyperplanes. Because of the importance of the characterisations of the production possibility sets in data envelopment analysis, we suggest two multi objective linear programming problems and then we identify some characterisations of the production possibility set by investigation of the relations among the suggested multi objective linear programming models and the input oriented envelopment and multiplier BCC models. In this paper, we use weighted sum and epsilon-constraint scalarisation methods to present some mathematical properties for finding some relations among the efficient solutions of the proposed multi objective linear programming models and the characteristics of the production possibility set and data envelopment analysis models.

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Efficiency status of a feasible solution in the Multi-Objective Integer Linear Programming problems: A DEA methodology

Cited by 19 publications

References 13 publications

Research on Logistics Efficiency of Chinese Ports above Designated Size Based on DEA-Malmquist Index

Research on Logistics Efficiency of Chinese Ports above Designated Size Based on DEA-Malmquist Index

Identifying optimal technological portfolios for European power generation towards climate change mitigation: A robust portfolio analysis approach

Characterisations of the production possibility set in data envelopment analysis: an MOLP approach

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