The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Min Zhang - One of the best experts on this subject based on the ideXlab platform.
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risk minimization regret minimization and progressive hedging algorithms
Mathematical Programming, 2020Co-Authors: Jie Sun, Xinmin Yang, Qiang Yao, Min ZhangAbstract:This paper begins with a study on the dual representations of risk and regret measures and their impact on modeling multistage decision making under uncertainty. A relationship between risk envelopes and regret envelopes is established by using the Lagrangian duality theory. Such a relationship opens a door to a decomposition scheme, called progressive hedging, for solving multistage risk minimization and regret minimization problems. In particular, the classical progressive hedging algorithm is modified in order to handle a new class of linkage constraints that arises from reformulations and other applications of risk and regret minimization problems. Numerical results are provided to show the efficiency of the progressive hedging algorithms.
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risk minimization regret minimization and progressive hedging algorithms
Research Papers in Economics, 2017Co-Authors: Jie Sun, Xinmin Yang, Qiang Yao, Min ZhangAbstract:Optimization models based on coherent and averse risk measures are of essential importance in financial management and business operations. This paper begins with a study on the dual representations of risk and regret measures and their impact on modeling multistage decision making under uncertainty. The relationship between risk envelopes and regret envelopes is established by using the Lagrangian duality theory. It is then pointed out that such a relationship opens a door to a decomposition scheme, called progressive hedging, for solving multistage risk minimization and regret minimization problems. In particular, the classical progressive hedging algorithm is modified in order to handle a new class of constraints that arises from a reformulation of risk and regret minimization problems. Numerical results are provided to show the efficiency of the progressive hedging algorithms.
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restricted p isometry properties of nonconvex matrix recovery
IEEE Transactions on Information Theory, 2013Co-Authors: Min Zhang, Zhenghai Huang, Ying ZhangAbstract:Recently, a nonconvex relaxation of low-rank matrix recovery (LMR), called the Schatten- p quasi-norm minimization (0 <; p <; 1), was introduced instead of the previous nuclear norm minimization in order to approximate the problem of LMR closer. In this paper, we introduce a notion of the restricted p-isometry constants (0 <; p ≤ 1) and derive a p -RIP condition for exact reconstruction of LMR via Schatten-p quasi-norm minimization. In particular, we determine how many random, Gaussian measurements are needed for the p-RIP condition to hold with high probability, which gives a theoretical result that it needs fewer measurements with small p for exact recovery via Schatten-p quasi-norm minimization than when p=1.
Vivian W Y Tam - One of the best experts on this subject based on the ideXlab platform.
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designers attitude and behaviour towards construction waste minimization by design a study in shenzhen china
Resources Conservation and Recycling, 2015Co-Authors: Vivian W Y Tam, Jian Zuo, Jiaolan ZhuAbstract:Abstract Construction waste presents a significant challenge to the sustainable development in the context of rapid urbanization. Although construction waste management has been implemented at different levels, there are limited studies on the role of design professionals particularly the implementation of waste minimization by design. This paper aims to examine the influence of designers’ attitude on their waste minimization behaviour and explores the predictors of designers’ implementing waste minimization by design. Based on Ajzen's theory of planned behaviour (TPB), a hypothetic model was developed, which was consequently tested via the structural equation modelling (SEM). A questionnaire survey was conducted to collect data in Shenzhen, Mainland China. Results showed that the designers’ attitude and perceived behavioural control have positive and significant effects on their behaviour on waste minimization. However, subjective norm plays a limited role. Moreover, the total effect of perceived behavioural control is notably greater than that of attitude on designers’ behaviour. Corresponding policies are proposed to facilitate waste minimization during the design process.
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critical factors in effective construction waste minimization at the design stage a shenzhen case study china
Resources Conservation and Recycling, 2014Co-Authors: Jiayua Wang, Vivian W Y TamAbstract:Abstract Construction waste minimization at the design stage is a key strategy in effective waste reduction. However, it seems that few studies focus on exploratory factors that can significantly improve the design of construction waste minimization. This paper addresses this research gap by presenting a set of critical factors that inform and improve the practice of waste minimization design, particularly in the context of Shenzhen, China. Nineteen potential factors which can influence effective waste minimization are presented based on related official guidelines, reports and literature. Top institutions in Shenzhen that have received a Grade A building design certification were surveyed through a questionnaire. From this survey, six critical factors are derived: (1) large-panel metal formworks, (2) prefabricated components, (3) fewer design modifications, (4) modular design, (5) waste reduction investment and (6) economic incentive. The applicability and significance of the identified critical factors for effectively designing waste minimization are also explored. These critical factors not only provide designers and project managers with a useful set of criteria for effective design strategies to reduce construction waste, but also serve as valuable references for the government to formulate related construction waste minimization regulations.
Jiangfeng Zhang - One of the best experts on this subject based on the ideXlab platform.
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optimal sampling plan for clean development mechanism lighting projects with lamp population decay
Applied Energy, 2014Co-Authors: Xiaohua Xia, Jiangfeng ZhangAbstract:This paper proposes a metering cost Minimisation model that minimises metering cost under the constraints of sampling accuracy requirement for clean development mechanism (CDM) energy efficiency (EE) lighting project. Usually small scale (SSC) CDM EE lighting projects expect a crediting period of 10 years given that the lighting population will decay as time goes by. The SSC CDM sampling guideline requires that the monitored key parameters for the carbon emission reduction quantification must satisfy the sampling accuracy of 90% confidence and 10% precision, known as the 90/10 criterion. For the existing registered CDM lighting projects, sample sizes are either decided by professional judgment or by rule-of-thumb without considering any optimisation. Lighting samples are randomly selected and their energy consumptions are monitored continuously by power meters. In this study, the sampling size determination problem is formulated as a metering cost Minimisation model by incorporating a linear lighting decay model as given by the CDM guideline AMS-II.J. The 90/10 criterion is formulated as constraints to the metering cost Minimisation problem. Optimal solutions to the problem minimise the metering cost whilst satisfying the 90/10 criterion for each reporting period. The proposed metering cost Minimisation model is applicable to other CDM lighting projects with different population decay characteristics as well.
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optimal sampling plan for clean development mechanism energy efficiency lighting projects
Applied Energy, 2013Co-Authors: Xiaohua Xia, Jiangfeng ZhangAbstract:Clean development mechanism (CDM) project developers are always interested in achieving required measurement accuracies with the least metering cost. In this paper, a metering cost Minimisation model is proposed for the sampling plan of a specific CDM energy efficiency lighting project. The problem arises from the particular CDM sampling requirement of 90% confidence and 10% precision for the small-scale CDM energy efficiency projects, which is known as the 90/10 criterion. The 90/10 criterion can be met through solving the metering cost Minimisation problem. All the lights in the project are classified into different groups according to uncertainties of the lighting energy consumption, which are characterised by their statistical coefficient of variance (CV). Samples from each group are randomly selected to install power meters. These meters include less expensive ones with less functionality and more expensive ones with greater functionality. The metering cost Minimisation model will minimise the total metering cost through the determination of the optimal sample size at each group. The 90/10 criterion is formulated as constraints to the metering cost objective. The optimal solution to the Minimisation problem will therefore minimise the metering cost whilst meeting the 90/10 criterion, and this is verified by a case study. Relationships between the optimal metering cost and the population sizes of the groups, CV values and the meter equipment cost are further explored in three simulations. The metering cost Minimisation model proposed for lighting systems is applicable to other CDM projects as well.
Rainer Leisten - One of the best experts on this subject based on the ideXlab platform.
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an efficient constructive heuristic for flowtime Minimisation in permutation flow shops
Omega-international Journal of Management Science, 2003Co-Authors: Jose M Framinan, Rainer LeistenAbstract:Abstract In this paper, we propose a heuristic for mean/total flowtime Minimisation in permutation flow shops. The heuristic exploits the idea of ‘optimising’ partial schedules, already present in the NEH-heuristic (Omega 11 (1983) 91) with respect to makespan Minimisation. We compare the proposed heuristic against the ones by Rajendran and Ziegler (Eur. J. Oper. Res. 32 (1994) 2541), and Woo and Yim (Comput. Oper. Res. 25 (1998) 175), which are considered the best constructive heuristics for flowtime Minimisation so far. The computational experiments carried out show that our proposal outperforms both heuristics with respect to the quality of the solutions. Moreover, our heuristic can be embedded in an improvement scheme to build a composite heuristic in the manner suggested by Allahverdi and Aldowaisan (Int. J. Prod. Econom. 77 (2002) 71) for the flowtime Minimisation problem. The so-constructed composite heuristic also improves the best results obtained by the original composite heuristics by Allahverdi and Aldowaisan.
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efficient heuristics for flowshop sequencing with the objectives of makespan and flowtime Minimisation
European Journal of Operational Research, 2002Co-Authors: Jose M Framinan, Rainer Leisten, Rafael RuizusanoAbstract:In this paper we analyse the performance of flowshop sequencing heuristics with respect to the objectives of makespan and flowtime Minimisation. For flowtime Minimisation, we propose the strategy employed by the NEH heuristic to construct partial solutions. Results show that this approach outperforms the common fast heuristics for flowtime Minimisation while performing similarly or slightly worse than others which, on reward, prove to be much more CPU time-consuming. Additionally, the suggested approach is well balanced with respect to makespan and flowtime Minimisation. Based on the previous results, two algorithms are proposed for the sequencing problem with multiple objectives – makespan and flowtime Minimisation. These algorithms provide the decision maker with a set of heuristically efficient solutions such that he/she may choose the most suitable sequence for a given ratio between costs associated with makespan and those assigned to flowtime. Computational experience shows both algorithms to perform better than the current heuristics designed for the two-criteria problem.
Jose M Framinan - One of the best experts on this subject based on the ideXlab platform.
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an efficient constructive heuristic for flowtime Minimisation in permutation flow shops
Omega-international Journal of Management Science, 2003Co-Authors: Jose M Framinan, Rainer LeistenAbstract:Abstract In this paper, we propose a heuristic for mean/total flowtime Minimisation in permutation flow shops. The heuristic exploits the idea of ‘optimising’ partial schedules, already present in the NEH-heuristic (Omega 11 (1983) 91) with respect to makespan Minimisation. We compare the proposed heuristic against the ones by Rajendran and Ziegler (Eur. J. Oper. Res. 32 (1994) 2541), and Woo and Yim (Comput. Oper. Res. 25 (1998) 175), which are considered the best constructive heuristics for flowtime Minimisation so far. The computational experiments carried out show that our proposal outperforms both heuristics with respect to the quality of the solutions. Moreover, our heuristic can be embedded in an improvement scheme to build a composite heuristic in the manner suggested by Allahverdi and Aldowaisan (Int. J. Prod. Econom. 77 (2002) 71) for the flowtime Minimisation problem. The so-constructed composite heuristic also improves the best results obtained by the original composite heuristics by Allahverdi and Aldowaisan.
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efficient heuristics for flowshop sequencing with the objectives of makespan and flowtime Minimisation
European Journal of Operational Research, 2002Co-Authors: Jose M Framinan, Rainer Leisten, Rafael RuizusanoAbstract:In this paper we analyse the performance of flowshop sequencing heuristics with respect to the objectives of makespan and flowtime Minimisation. For flowtime Minimisation, we propose the strategy employed by the NEH heuristic to construct partial solutions. Results show that this approach outperforms the common fast heuristics for flowtime Minimisation while performing similarly or slightly worse than others which, on reward, prove to be much more CPU time-consuming. Additionally, the suggested approach is well balanced with respect to makespan and flowtime Minimisation. Based on the previous results, two algorithms are proposed for the sequencing problem with multiple objectives – makespan and flowtime Minimisation. These algorithms provide the decision maker with a set of heuristically efficient solutions such that he/she may choose the most suitable sequence for a given ratio between costs associated with makespan and those assigned to flowtime. Computational experience shows both algorithms to perform better than the current heuristics designed for the two-criteria problem.
