关键词：
Nonclassical diffusion equation;time-dependent global attractor;nonlinear delay;arbitrary polynomial growth
摘要：
In this paper, we mainly investigate the asymptotic behavior of solutions for the nonclassical diffusion problem with hereditary effects and time-dependent perturbed parameter. The main novelty is that the delay term may be driven by a function under very minimal assumptions, namely, measurability and the fact that the phase space is a time-dependent space of functions that are continuous in time. The existence and regularity of time-dependent global attractors are proved by using a new analytical technique. It is remarkable that the nonlinearity $ f $ has no restriction on the upper growth.
摘要：
The digital economy and digital technology are promoting the integrated development of industry and digital, forming a new path for industrial upgrading and building a new development pattern.In today's context of digital economy and green transformation, it is a challenging optimization problem to scientifically plan the logistics routes of electric vehicles (EVs) when taking charging strategies into consideration. Aiming at the drawback of supposing a fixed charging rate in the traditional EV routing problems (EVRPs), the charging data of a type of mainstream EVs were collected and the instantaneous charging power was simulated in the real scenario. To solve problems of the fixed charge timing and charged energy in traditional EVRP models and partial charging strategies, a new EVRP model considering the flexible charging strategy (EVRP-FCS) by taking the charged energy as one of the decision variables. To effectively solve the model and fully search in the solution space, an improved evolutionary algorithm was proposed. The performance advantages of the algorithm are determined by comparison of 22 groups of large-scale experimental examples. The experimental results have demonstrated the performance advantages of the algorithm.
The digital economy and digital technology are promoting the integrated development of industry and digital, forming a new path for industrial upgrading and building a new development pattern.In today's context of digital economy and green transformation, it is a challenging optimization problem to scientifically plan the logistics routes of electric vehicles (EVs) when taking charging strategies into consideration. Aiming at the drawback of supposing a fixed charging rate in the traditional EV routing problems (EVRPs), the charging data of a type of mainstream EVs were collected and the instantaneous charging power was simulated in the real scenario. To solve problems of the fixed charge timing and charged energy in traditional EVRP models and partial charging strategies, a new EVRP model considering the flexible charging strategy (EVRP-FCS) by taking the charged energy as one of the decision variables. To effectively solve the model and fully search in the solution space, an improved evolutionary algorithm was proposed. The performance advantages of the algorithm are determined by comparison of 22 groups of large-scale experimental examples. The experimental results have demonstrated the performance advantages of the algorithm.
作者机构：
[Huang, Qian; Pan, Shuangli; Liao, Huiyu; Jiang, Zehua] Cent South Univ Forestry & Technol, Sch Logist, Changsha, Hunan, Peoples R China.;[Zheng, Guijun] Cent South Univ Forestry & Technol, Business Sch, Changsha, Hunan, Peoples R China.;[Pan, Shuangli] Hunan Key Lab Intelligent Logist Technol, Changsha, Hunan, Peoples R China.
通讯机构：
[Pan, SL ] C;Cent South Univ Forestry & Technol, Sch Logist, Changsha, Hunan, Peoples R China.;Hunan Key Lab Intelligent Logist Technol, Changsha, Hunan, Peoples R China.
摘要：
The effective circulation of fresh agricultural products is conducive to increasing farmers' income and improving the living standards of urban residents. Cold chain storage facilities in agricultural producing areas play an important role in ensuring the quality of agricultural products, extending the freshness period of goods, and improving logistics efficiency. Different types of fresh produce have different requirements for refrigeration and often require transshipment due to quantity constraints. In addition, there are economies of scale in the construction and operation of cold chain storage facilities. Based on the above considerations, with the aim of minimizing the total daily cost, an optimization model for the layout of multi-level cold chain storage facilities is established to determine the number, location, type and capacity of cold chain storage facilities at the same time. Genetic algorithm is chosen to solve the model according to the characteristics of the model. Taking J County of China as an example, the model is proved to have strong operability and applicability. It is of guiding significance and reference value to optimize the layout of cold chain storage facilities in rural areas.
摘要：
An Electric Vehicle (EV) is an appropriate substitution for traditional transportation means for diminishing greenhouse gas emissions. However, decision-makers are beset by the limited driving range caused by the low battery capacity and the long recharging time. To resolve the former issue, several transportation companies increases the travel distance of the EV by establishing recharging stations in various locations. The proposed Electric Vehicle-Routing Problem with Time Windows (E-VRPTW) and recharging stations are constructed in this context; it augments the VRPTW by reinforcing battery capacity constraints. Meanwhile, super-recharging stations are gradually emerging in the surroundings. They can decrease the recharging time for an EV but consume more energy than regular stations. In this paper, we first extend the E-VRPRTW by adding the elements of super-recharging stations. We then apply a two-stage heuristic algorithm driven by a dynamic programming process to solve the new proposed problem to minimize the travel and total recharging costs. Subsequently, we compare the experimental results of this approach with other algorithms on several sets of benchmark instances. Furthermore, we analyze the impact of super-recharging stations on the total cost of the logistic plan.
期刊：
Expert Systems with Applications,2024年261:125532 ISSN：0957-4174
通讯作者：
Ruihuan Liu
作者机构：
[Zhao, Chengwei] School of Business, Central South University of Forestry and Technology, Changsha, China;[Liu, Ruihuan] School of Logistics, Central South University of Forestry and Technology, Changsha, China;[Xu, Xuanhua; He, Jishan] School of Business, Central South University, Changsha, China
通讯机构：
[Ruihuan Liu] S;School of Logistics, Central South University of Forestry and Technology, Changsha, China
摘要：
This paper considers a dual-channel supply chain where the supplier can distribute products through an online platform and a capital-constrained traditional offline retailer. The retailer needs to fund its business by a portfolio financing of trade credit and platform investment to enter the market. With the price-dependent market uncertain demand, the supplier faces choices among direct, traditional, and dual channels for product distribution. We use the CVaR criterion to formulate the retailer’s risk-averse behaviour. Then derive the optimal retail channel strategy in a Stackelberg game model where the platform leads by setting a revenue-sharing rate. Our results unveil a Pareto improvement region in revenue sharing rates within the portfolio financing scheme. As the slotting fee escalates, the supplier tends towards traditional channels. Conversely, with a modest slotting fee, a threshold emerges for the retailer’s risk aversion, delineating the optimal retail channel. High retailer risk aversion favours the dual channel, while lower aversion steers all members towards the direct channel. Theoretical findings are validated through numerical analysis.
作者机构：
[Zhang, Yinggui; Mo, Weiwei; Xiao, Yang; Wu, Caiyi] Cent South Univ, Sch Traff & Transportat Engn, Changsha 410075, Peoples R China.;[Xiao, Yuxie] Changsha Planning & Design Inst Co Ltd, Engn Consulting Dept, Changsha 410011, Peoples R China.;[Wang, Juan] Cent South Univ Forestry & Technol, Sch Logist, Changsha 410004, Peoples R China.
通讯机构：
[Wang, J ] C;Cent South Univ Forestry & Technol, Sch Logist, Changsha 410004, Peoples R China.
关键词：
oversize and heavyweight cargo;carbon emission;multimodal transportation;genetic algorithm
摘要：
With the increasing global concern over climate change, reducing greenhouse gas emissions has become a universal goal for governments and enterprises. For oversize and heavyweight cargo (OHC) transportation, multimodal transportation has become widely adopted. However, this mode inevitably generates carbon emissions, making research into effective emission reduction strategies essential for achieving low-carbon economic development. This study investigates the optimization of multimodal transportation paths for OHC (OMTP-OHC), considering various direct carbon pricing policies and develops models for these paths under the ordinary scenario-defined as scenarios without any carbon pricing policies-and two carbon pricing policy scenarios, namely the emission trading scheme (ETS) policy and the carbon tax policy, to identify the most cost-effective solutions. An enhanced genetic algorithm incorporating elite strategy and catastrophe theory is employed to solve the models under the three scenarios. Subsequently, we examine the impact of ETS policy price fluctuations, carbon quota factors, and different carbon tax levels on decision-making through a case study, confirming the feasibility of the proposed model and algorithm. The findings indicate that the proposed algorithm effectively addresses this problem. Moreover, the algorithm demonstrates a small impact of ETS policy price fluctuations on outcomes and a slightly low sensitivity to carbon quota factors. This may be attributed to the relatively low ETS policy prices and the characteristics of OHC, where transportation and modification costs are significantly higher than carbon emission costs. Additionally, a comparative analysis of the two carbon pricing policies demonstrates the varying intensities of emission reductions in multimodal transportation, with the ranking of carbon emission reduction intensity as follows: upper-intermediate level of carbon tax > intermediate level of carbon tax > lower-intermediate level of carbon tax = ETS policy > the ordinary scenario. The emission reduction at the lower-intermediate carbon tax level (USD 8.40/t) matches that of the ETS policy at 30%, with a 49.59% greater reduction at the intermediate level (USD 50.48/t) compared to the ordinary scenario, and a 70.07% reduction at the upper-intermediate level (USD 91.14/t). The model and algorithm proposed in this study can provide scientific and technical support to realize the low-carbonization of the multimodal transportation for OHC. The findings of this study also provide scientific evidence for understanding the situation of multimodal transportation for OHC under China's ETS policy and its performance under different carbon tax levels in China and other regions. This also contributes to achieving the goal of low-carbon economic development.
关键词：
Green computing;Cloud workflow;Large-scale scheduling;Evolutionary algorithm;Multi-objective optimization
摘要：
Energy consumption and makespan of workflow execution are two core performance indicators in operating cloud platforms. But, simultaneously optimizing these two indicators encounters various challenges, such as elastic resources, large-scale decision variables, and sophisticated workflow structures. To handle these challenges, we design an adaptive evolutionary scheduling algorithm , namely AESA, with three innovative strategies. First, a heuristic population initialization strategy is devised to gather workflow tasks onto limited potential resources, thereby alleviating the negative impact of redundant cloud resources on evolutionary search efficiency. Then, a variable analysis strategy is designed to dynamically measure the contribution of each decision variable in pushing the population towards Pareto-optimal fronts. Moreover, AESA embraces an adaptive strategy to reward more evolutionary opportunities for decision variables with higher contributions to handle large-scale decision variables in a targeted manner, further improving the efficiency of evolutionary search. Finally, extensive experiments are performed based on real-world cloud platforms and workflow traces to verify the effectiveness of the proposed AESA. The comparison results validate its superior performance by significantly outperforming five representative baselines in optimizing makespan and energy consumption. Also, the results of ablation experiments demonstrate that all three components contribute to AESA’s overall performance, with the adaptive reward mechanism being the most significant.
Energy consumption and makespan of workflow execution are two core performance indicators in operating cloud platforms. But, simultaneously optimizing these two indicators encounters various challenges, such as elastic resources, large-scale decision variables, and sophisticated workflow structures. To handle these challenges, we design an adaptive evolutionary scheduling algorithm , namely AESA, with three innovative strategies. First, a heuristic population initialization strategy is devised to gather workflow tasks onto limited potential resources, thereby alleviating the negative impact of redundant cloud resources on evolutionary search efficiency. Then, a variable analysis strategy is designed to dynamically measure the contribution of each decision variable in pushing the population towards Pareto-optimal fronts. Moreover, AESA embraces an adaptive strategy to reward more evolutionary opportunities for decision variables with higher contributions to handle large-scale decision variables in a targeted manner, further improving the efficiency of evolutionary search. Finally, extensive experiments are performed based on real-world cloud platforms and workflow traces to verify the effectiveness of the proposed AESA. The comparison results validate its superior performance by significantly outperforming five representative baselines in optimizing makespan and energy consumption. Also, the results of ablation experiments demonstrate that all three components contribute to AESA’s overall performance, with the adaptive reward mechanism being the most significant.
摘要：
This paper analyzes the static resilience of global wood forest products trade networks across upstream, midstream, downstream, and recycling sectors using a complex directed weighted network approach. By examining topological features and resilience from 2002 to 2021, this study reveals significant structural evolution and scale expansion in these networks. It finds improvements in network efficiency and resilience, alongside an increase in weighted hierarchy highlighting the prominent roles of core countries like China, the US, and Germany. While these countries bolster network resilience, they also introduce certain vulnerabilities. This study finds notable disassortative mixing without trade volume weights and diversified trends with weights, offering new insights into network dynamics. Core nodes must address disruption risks, enhance diversity, and establish emergency response mechanisms. In the recycling sector, this paper highlights weak trade connections and low resilience, with the US maintaining dominance, China’s influence waning, and India’s rapid ascent. This paper concludes by emphasizing the need for refined indicator systems and deeper explorations into resilience enhancement strategies for operational and targeted suggestions.
摘要：
To address the limitation of inflexible dimension parameters in thin-walled structures for ensuring energy absorption effectiveness, a design approach for a multi-tube combination of Corrugated Spacer Tubes (CST) based on a height difference staggered compensation method was proposed. The theoretical and finite element models of CST were established, and the accuracy of both models was validated through experiments. Based on the theoretical model, a design approach for the CST multi-tube combination was presented. By sequentially selecting the structural parameters of CST to induce stable and ordered circumferential deformation, consistent peak impact forces and equal intervals were ensured during axial compression. Subsequently, different CSTs with the same properties were distributed at different heights with offsets, causing the peak impact forces of different tubes to be uniformly distributed as designed within a folding wavelength, achieving a staggered compensation effect for overall smooth energy absorption. Building on this, six combination tubes were designed, and finite element models were established. The results indicate that compared to regular combination tubes, the load fluctuation of the height difference combination tubes was significantly reduced by approximately 80 %, with no significant loss in energy absorption, specific energy absorption, or mean crushing force. Moreover, the initial peak impact force was also moderately reduced. Furthermore, as the wall thickness of the CST corrugated part increased, the specific energy absorption improved by 61.5 % and 34.7 %, while the load fluctuation remained consistently low, demonstrating the effectiveness of this method in separating and compensating for CST peak impact forces.
To address the limitation of inflexible dimension parameters in thin-walled structures for ensuring energy absorption effectiveness, a design approach for a multi-tube combination of Corrugated Spacer Tubes (CST) based on a height difference staggered compensation method was proposed. The theoretical and finite element models of CST were established, and the accuracy of both models was validated through experiments. Based on the theoretical model, a design approach for the CST multi-tube combination was presented. By sequentially selecting the structural parameters of CST to induce stable and ordered circumferential deformation, consistent peak impact forces and equal intervals were ensured during axial compression. Subsequently, different CSTs with the same properties were distributed at different heights with offsets, causing the peak impact forces of different tubes to be uniformly distributed as designed within a folding wavelength, achieving a staggered compensation effect for overall smooth energy absorption. Building on this, six combination tubes were designed, and finite element models were established. The results indicate that compared to regular combination tubes, the load fluctuation of the height difference combination tubes was significantly reduced by approximately 80 %, with no significant loss in energy absorption, specific energy absorption, or mean crushing force. Moreover, the initial peak impact force was also moderately reduced. Furthermore, as the wall thickness of the CST corrugated part increased, the specific energy absorption improved by 61.5 % and 34.7 %, while the load fluctuation remained consistently low, demonstrating the effectiveness of this method in separating and compensating for CST peak impact forces.
摘要：
The constrained-domination principle (CDP) is one of the most popular constraint-handling techniques (CHTs), since it is simple, nonparametric, and easily embedded in unconstrained multiobjective evolutionary algorithms (MOEAs). However, the CDP overly emphasizes the importance of feasibility, which may lead to the search getting stuck in some locally feasible regions or locally optimal, especially when encountering problems with discontinuous and/or narrow feasible regions. This article seeks to capitalize on the strengths of the CDP while overcoming its weaknesses. Accordingly, we propose a novel constrained MOEA (called MOEA/D-LCDP), in which the CDP is applied in a local manner. Unlike most CHTs that emphasize feasibility, which use the feasibility rule in the whole search space, the proposed localized CDP only adopts the CDP within the niche. That is, to maintain the diversity of the population, only solutions within the niche are compared based on the localized CDP. The niche radius is determined a priori by the acute angle between the current subproblem and its nearest subproblem. Additionally, a population-based status detection strategy is developed to allocate computing resources more rationally, and a diversity-enhanced CDP is designed to enhance the exploitation of the search. Comprehensive experiments conducted on four benchmark test suites with a total of 34 problems and three real-world applications demonstrate that MOEA/D-LCDP is very competitive with representative algorithms.
作者机构：
[Yan, Hongyu; Xie, Suchao; Jing, Kunkun; Wang, Hao] Cent South Univ, Key Lab Traff Safety Track, Minist Educ, Changsha, Peoples R China.;[Yan, Hongyu; Xie, Suchao; Jing, Kunkun; Wang, Hao] Cent South Univ, Sch Traff & Transportat Engn, Changsha, Peoples R China.;[Zhou, Hui] Cent South Univ Forestry & Technol, Sch Logist & Transportat, Changsha, Peoples R China.;[Xie, SC; Xie, Suchao] Cent South Univ, Key Lab Traff Safety Track, Minist Educ, Changsha 410075, Peoples R China.
通讯机构：
[Xie, SC ] C;Cent South Univ, Key Lab Traff Safety Track, Minist Educ, Changsha 410075, Peoples R China.
关键词：
dual-scale RVE model;homogenization analysis;visualization and adjustment of elastic modulus
摘要：
Utilizing computer tomography (CT) to obtain detailed parameter models, we established a dual‐scale model comprising experimentally validated microscopic (RVE) and macroscopic RVE. We assessed the impact of yarn fiber volume fraction and weaving distance on the elastic properties of the yarn and provided a formula that combines these two factors to adjust the in‐plane orthogonal Young's modulus. Abstract Three‐dimensional (3D) orthogonal woven composites can overcome the drawback of weak interlaminar strengths in traditional laminated composites and exhibit excellent resistance to out‐of‐plane impact, however, the significant difference in properties in the in‐plane orthogonal direction will limit the potential range of application thereof. Predicting elastic properties and exploring methods of adjustment are therefore of paramount importance. Using computed tomography (CT) scanning to obtain detailed parameter models, a corresponding dual‐scale model of microscopic representative volume element (RVE) and mesoscopic RVE was established, and the accuracy of the model was experimentally validated, which can predict the elastic properties of materials. In addition, the influences of the yarn fiber volume fraction and weaving distance on elastic properties were evaluated using the elastic modulus visualization method, and a formula integrating these two factors is provided for adjustment of the in‐plane orthogonal Young's modulus. Highlights Experimentally validated microscale and mesoscale RVE models were established. The influences of factors on elastic properties were visualized. The relationship between Young's modulus and influencing factors was derived. A reliable strategy for adjusting the in‐plane Young's modulus was proposed.
