DORA
DORA (De Montfort Open Research Archive) is De Montfort University's research repository. It forms the primary public and institutional record of DMU research outputs. The breadth of research at DMU means that these outputs include articles, conference papers, books, book chapters, and other material available in a digital form. The record for each item contains descriptive information as well as, where possible, a version of the final research output. DORA also provides access to DMU PhD theses. This includes most PhD produced from 2009 onwards.
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Recent Submissions
Validation of a meso-scale Urban Building Energy Model of domestic heat demand in England and Scotland
(Building Digital Twin Scientific Conference 2025, 2025-04-30) Bustamante, Javier Sandoval; Khattak, Sanober
This article presents a methodology to model domestic peak heating load and annual heat demand at the urban scale using geospatial data and building stock data from Energy Performance Certificates (EPC). The model was run on 720269 domestic properties across three different local authorities in Scotland (Aberdeen City, Dundee City Council and Fife) and two combined authorities in England (Somerset Council and West Midlands Combined Authority). Then, the results were validated on a mean absolute percentage error (MAPE) basis against smart meter gas demand readings from 4397 properties included in the Smart Energy Research Lab (SERL) Statistical data set. The model was able to predict peak heating load with a 4% MAPE in F-rated properties in Fife and annual heat demand with a 6% MAPE in A-rated properties in Somerset Council. However, the reported MAPE goes as high as 70% for peak heating load and 57% for annual heat demand. Further validation on an aggregated basis is required against a comprehensive data set that includes separate gas demand readings for space and hot water heating.
A variable window multi-interval rescheduling optimization algorithm for dynamic flexible job shop problem
(Elsevier, 2025-04-21) Guo, Zeyin; Wei, Lixin; Li, Xin; Yang, Shengxiang; Zhang, Jinlu
The dynamic flexible workshop scheduling problem (DFJSP) requires the generation of new scheduling plans after being subjected to dynamic disturbances. Due to the reconfigurability of chromosomal gene, scheduling schemes have a large search space, which poses challenges for solving scheduling schemes. Therefore, a variable window multi-interval optimization (VWMI) rescheduling algorithm is proposed to solve the DFJSP. A nonlinear adaptive crossover probability and mutation probability function is proposed to address the issue of combinatorial optimization easily getting stuck in local optima. Based on the mapping relationship between individual space and objective space, a spatial joint selection method is proposed to select diverse individuals. Compared with other algorithms in dynamic workshop test cases, the rescheduling strategy achieved 7 optimal performance values in 15 test cases, with a maximum time efficiency improvement of 30.2%. In addition, the VWMI achieved 11 good performances in test cases, outperforming other optimization methods.
A grey incidence model with fractional cumulative time delay effects and its applications
(Elsevier, 2025-04-18) Sun, Jing; Dang, Yaoguo; Yang, Shengxiang; Wang, Junjie; Cai, Ying
To identify the time-delay relationship between sequences more accurately, we propose a grey incidence model for time-delay systems. Before constructing the new model, we first clarify several time-delay relationships, including instantaneous form and cumulative form. Subsequently, the Weibull distribution is initially used to represent multiple types of time-delay effects. To reduce the computational load, the minimum cumulative step size is designed to simplify convolution, which is used to aggregate cumulative time delay effects in our research. This facilitates us to extract discrepancy information using relative angles and distances. To streamline the process of obtaining results, we utilize particle swarm optimization to optimize the self-adaptive parameters of the Weibull distribution and obtain cumulative time-delay information. The proposed model is validated through numerical experiments to analyze the time-delay effects of key influencing factors on air pollution. Finally, a comparative analysis with ten prevailing models demonstrates that our model not only integrates the functionalities of traditional models but also exhibits significant advantages in the detection of continuous time delay.
A transformation method of non-cooperative to cooperative behavior by trust propagation in social network group decision making
(IEEE, 2025-04-04) Gai, Tiantian; Chiclana, Francisco; Jin, Weidong; Zhou, Mi; Wu, Jian
In the consensus reaching process (CRP) of social network group decision making (SN-GDM), the non-cooperative behavior exhibited by experts will hinder the achievement of group consensus. This paper develops a non-cooperative behavior management framework based on trust propagation and dynamic cooperation index under bidirectional feedback context. On the one hand, a trust propagation operator with trust decay is established to enhance the trust relationship between non-cooperative experts; On the other hand, the fuzzy preference relations are utilized as preference expression structure, and the mutual reinforcing effect between consensus and trust is explored to achieve the dynamic enhancement of cooperation index, thereby facilitating the transformation of non-cooperative behavior. Specifically, a cooperation index is formulated to identify the non-cooperation behavior. Subsequently, a non-cooperative behavior transformation method by dynamic cooperation index is investigated. Finally, a bidirectional feedback mechanism is provided for group consensus reaching. This paper provides an innovative strategy for detecting and managing non-cooperative behavior, an illustrative example and some analyses are presented to verify the validity of proposed method.
An inter-subgroup compensation mechanism by Nash bargaining game for managing non-cooperative behavior in group decision making
(Elsevier, 2025-04-19) Yang, Jie; Wu, Jian; Chiclana, Francisco; Cao, Mingshuo; Yager, Ronald R.
Non-cooperative behavior exhibited by DMs when they must make excessive interest compromises hinders the achievement of group consensus. This study develops an inter-subgroup compensation mechanism using the Nash bargaining game under the minimum cost consensus model (MCCM) framework to managing non-cooperative behavior. First, a cooperative acceptability index (CAI) based on compromise limit costs is proposed to objectively identify non-cooperative behavior. By quantifying the acceptable compromise limit costs, the CAI ensures that consensus adjustments remain within acceptable bounds. Then, an inter-subgroup compensation mechanism is designed using the Nash bargaining game from the perspective of Kaldor–Hicks improvement. This mechanism enables cooperative DMs to incentivize non-cooperative peers via resource transfers, achieving dual optimization by minimizing collective costs and ensuring individual acceptability. Finally, a community renewal application example and comparison analysis are provided to illustrate the efficacy of the proposed approach.