Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing industry.General DFJSP research only considers machine constraints and ignores worker constraints.As one critical factor of production,effective utilization of worker resources can increase productivity.Meanwhile,energy consumption is a growing concern due to the increasingly serious environmental issues.Therefore,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this paper.To solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling schemes.To further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are proposed.These strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto solutions.The effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 instances.The results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

Resource constraints and firm innovation:When less is more?

This paper explores the relationship between resource constraints and innovation of new firms.Drawing upon the relevant literature,we incorporate resource constraints as the antecedent to the bricolage-innovation link.Compared to prior studies that treated resource constraints as a one-dimensional variable,we operationalize it along two dimensions:knowledge constraints and financial constraints.Our argument posits that knowledge constraints and financial constraints act as catalysts for innovation in new firms,with bricolage serving as a mediating role.To test our hypotheses,we conducted a survey involving 183 entrepreneurs in the United States.The data analysis demonstrates that bricolage fully mediates the relationship between knowledge con‐straints and innovation and partially mediates the relationship between financial constraints and innovation.Theoretical and practical implications are discussed.

A Preliminary Analysis of Land Resource Constraints on Urban Expansion of Beijing Based on Land Supply and Demand

Land resources not only provide support for urban development, but play a feedback and restricting role in unregulated urban growth. Taking Beijing City as an example, this paper analyzes supply and demand relationships and upper limits for the growth of land resources during the process of urban development. By analyzing dominant factors and trends in the demand for land resources, this paper gives preliminary estimates on the minimum size of the land demand in Beijing in view of constructing a World City. According to the basic characteristics of supply and demand relationships for land, current land use in Beijing is confronting a grim situation of conflict between supply and demand. We also point out maximum growth and three types of constraints on land resources. Last, we propose solutions to resource and environmental bottlenecks, and urban disease amid urban development.

Optimizing Resource Management for IoT Devices in Constrained Environments

Embedded computing device implementation on the Internet of Things (IoT) requires careful assessment of their intrinsic resource limitations. These constraints are not limited to memory and processing capabilities but extend to the network interfaces, particularly due to the low-power radio standards that these devices typically employ. The IPv6 protocol is shown to be a strong option for guaranteeing interoperability in the IoT, mostly because of its large address space, the range of current IP-based protocols, and its intrinsic versatility. Considering these benefits, we investigate if current IP-based network management protocols can be implemented on devices with limited resources. We investigate the resource needs in particular for implementing Network Configuration Protocol (NETCONF) and Simple Network Management Protocol (SNMP) on an 8-bit AVR-based device. Our investigation reveals the specific memory and processing demands of these protocols, providing valuable insights into their practicality and efficiency in constrained IoT environments. This study underscores the potential and challenges of leveraging IPv6-based network management protocols to enhance the functionality and interoperability of IoT devices while operating within stringent resource limitations.

Image categorization with resource constraints： introduction, challenges and advances

As one of the most classic fields in computer vi- sion, image categorization has attracted widespread interests. Numerous algorithms have been proposed in the community, and many of them have advanced the state-of-the-art. How- ever, most existing algorithms are designed without consider- ation for the supply of computing resources. Therefore, when dealing with resource constrained tasks, these algorithms will fail to give satisfactory results. In this paper, we provide a comprehensive and in-depth introduction of recent develop- ments of the research in image categorization with resource constraints. While a large portion is based on our own work, we will also give a brief description of other elegant algo- rithms. Furthermore, we make an investigation into the re- cent developments of deep neural networks, with a focus on resource constrained deep nets.

Gini Coefficient-based Task Allocation for Multi-robot Systems With Limited Energy Resources

Nowadays, robots generally have a variety of capabilities, which often form a coalition replacing human to work in dangerous environment, such as rescue, exploration, etc. In these operating conditions, the energy supply of robots usually cannot be guaranteed. If the energy resources of some robots are consumed too fast, the number of the future tasks of the coalition will be affected. This paper will develop a novel task allocation method based on Gini coefficient to make full use of limited energy resources of multi-robot system to maximize the number of tasks. At the same time, considering resources consumption,we incorporate the market-based allocation mechanism into our Gini coefficient-based method and propose a hybrid method,which can flexibly optimize the task completion number and the resource consumption according to the application contexts.Experiments show that the multi-robot system with limited energy resources can accomplish more tasks by the proposed Gini coefficient-based method, and the hybrid method can be dynamically adaptive to changes of the work environment and realize the dual optimization goals.

Scheduling Model and Algorithm of Construction Equipment under Milestone Constraint

The scheduling of construction equipment is a means to realize network planning.With the large-scale and low-cost requirements of engineering construction,the cooperation among members of the engineering supply chain has become very important,and effective coordination of project plans at all levels to optimize the resource management and scheduling of a project is helpful to reduce project duration and cost.In this paper,under the milestone constraint conditions,the scheduling problems of multiple construction devices in the same sequence of operation were described and hypothesized mathematically,and the scheduling models of multiple equipment were established.The Palmer algorithm,CDS algorithm and Gupta algorithm were respectively used to solve the optimal scheduling of construction equipment to achieve the optimization of the construction period.The optimization scheduling of a single construction device and multiple construction devices was solved by using sequencing theory under milestone constraint,and these methods can obtain reasonable results,which has important guiding significance for the scheduling of construction equipment.

An effective estimation of distribution algorithm for parallel litho machine scheduling with reticle constraints

In order to improve the scheduling efficiency of photolithography,bottleneck process of wafer fabrications in the semiconductor industry,an effective estimation of distribution algorithm is proposed for scheduling problems of parallel litho machines with reticle constraints,where multiple reticles are available for each reticle type.First,the scheduling problem domain of parallel litho machines is described with reticle constraints and mathematical programming formulations are put forward with the objective of minimizing total weighted completion time.Second,estimation of distribution algorithm is developed with a decoding scheme specially designed to deal with the reticle constraints.Third,an insert-based local search with the first move strategy is introduced to enhance the local exploitation ability of the algorithm.Finally,simulation experiments and analysis demonstrate the effectiveness of the proposed algorithm.

Integrated assessment model of water resources constraint intensity on urbanization in arid area

Water has become a key restricting factor of the urbanization process in developing arid areas.Based on qualitative and quantitative methods,we constructed an integrated in-dicator system to assess the status of water resources and urbanization system in arid area,and established an AHP model reformed by entropy technology to evaluate the temporal and spatial variations of water resources constraint intensity on urbanization.This model is ap-plied to the Hexi Corridor,a typical arid area in NW China.Results show that,water resources constraint intensity on urbanization in the Hexi Corridor is bigger in the east and smaller in the west.It has changed from the less strong constraint type into the strong constraint type from 1985 to 2005,yet it decreased appreciably in recent years.At present,most areas in the Hexi Corridor belong to the less strong or strong constraint type.Through rational adjustment of water resources and urbanization system,the Hexi Corridor can still promote water resources sustainable utilization and accelerate the urbanization process.This study suggests that the integrated assessment model of water resources constraint intensity on urbanization is an effective method to analyze the conflicts between water resources and urbanization system in arid area.

Improved differential evolution algorithm for resource-constrained project scheduling problem

An improved differential evolution（IDE）algorithm that adopts a novel mutation strategy to speed up the convergence rate is introduced to solve the resource-constrained project scheduling problem（RCPSP）with the objective of minimizing project duration Activities priorities for scheduling are represented by individual vectors and a senal scheme is utilized to transform the individual-represented priorities to a feasible schedule according to the precedence and resource constraints so as to be evaluated.To investigate the performance of the IDE-based approach for the RCPSP,it is compared against the meta-heuristic methods of hybrid genetic algorithm（HGA）,particle swarm optimization（PSO） and several well selected heuristics.The results show that the proposed scheduling method is better than general heuristic rules and is able to obtain the same optimal result as the HGA and PSO approaches but more efficient than the two algorithms.

Minimal feasible sets in variable resource constrained projects

To determine the reasonable resource dependent relations between activities for the purpose of exactly computing the total floats and the free floats of activities, correctly identifying critical activities and critical sequences in a project schedule with variable resource constraints, the concept of the minimal feasible set （MFS） is proposed and the properties of MFS are discussed. The methods to identify optimal MFSs and resource links are then studied. Furthermore, MFS is generalized to the situation that the preconditions of MFS are not satisfied. Contrastive results show that in establishing resource links and resolving floats, MFS is at least not inferior to other methods in all cases and is superior in most situations.

Concurrent processes scheduling with scarce resources in small and medium enterprises

Scarce resources,precedence and non-determined time-lag are three constraints commonly found in small and medium manufacturing enterprises(SMEs),which are deemed to block the application of workflow management system(WfMS). To tackle this problem,a workflow scheduling approach is proposed based on timing workflow net(TWF-net) and genetic algorithm(GA). The workflow is modelled in a form of TWF-net in favour of process simulation and resource conflict checking. After simplifying and reconstructing the set of workflow instance,the conflict resolution problem is transformed into a resource-constrained project scheduling problem(RCPSP),which could be efficiently solved by a heuristic method,such as GA. Finally,problems of various sizes are utilized to test the performance of the proposed algorithm and to compare it with first-come-firstserved(FCFS) strategy. The evaluation demonstrates that the proposed method is an overwhelming and effective approach for scheduling the concurrent processes with precedence and resource constraints.

A New Uniform-based Resource Constrained Total Project Float Measure （U-RCTPF）

Resource scheduling has become one of the most important activities in project management research and practice in the last decades. Recently, as part of this development, formal tools and techniques were developed to tackle the more complex problem of resource allocation or scheduling; that is, making sure both time constraints and resource constraints are met. In project scheduling, the concept of float and criticality plays a central role, however, the recent literature does not offer a general and useful measure for criticality （flexibility） in resource constrained projects. The resource constrained project total float measure （RCTPF） is defined as the sum of the total floats of activities, where the total float for an activity is defined as the difference of its latest and earliest start times. The RCTPF calculates the total float of each activity in order to maximize the total float of the project. However, not only the existence of float or its amount is important, but in many cases the distribution of the total amount of the float within the activities is even more significant. The following paper presents an extended measure to the existing RCTPF measure to solve this problem. The new measure, uniform-based resource constrained total project float measure （U-RCTPF）, is geared toward the uniform distribution of the project total float among the various project activities. The scheduling objective is to minimize the variation of the float among the activities. In this approach, a resource-constrained project is characterized by its best schedule, where best means a schedule in which the RCTPF is maximal and the uniformly measure is minimal.

System resource constraint theory

The System Resource Constraint Theory intends to research growth of economy under different classes of system resource constraint. By analogy between ecology system and economic system, from the angle of total nature resource, total supply ability and total market volume, the theory focuses on the constraint condition and development characteristic of economy as well as the various game characteristics among economies such as independence, competition, and joint competition. According to the math deduction, the author finds that Logistic model is relative with Marthus＇s model and Zero-growth model.

Mixed Self-adapting GA Optimal Scheduling Algorithm for a Multiple Resource Job-shop

With an aim at the job-shop scheduling problem of multiple resource constraints, this paper presents mixed self-adapting Genetic Algorithm （ GA ） , and establishes a job-shop optimal scheduling model of multiple resource constraints based on the effect of priority scheduling rules in the heuristic algorithm upon the scheduling target. New coding regulations or rules are designed. The sinusoidal function is adopted as the self-adapting factor, thus making cross probability and variable probability automatically change with group adaptability in such a way as to overcome the shortcoming in the heuristic algorithm and common GA, so that the operation efficiency is improved. The results from real example simulation and comparison with other algorithms indicate that the mixed self-adapting GA algorithm can well solve the job-shop optimal scheduling problem under the constraints of various kinds of production resources such as machine-tools and cutting tools.

Regional Differentiation and Classification for Carrying Constraints on the Resources and Environment of China

Research on the relationship between national resource constraint-region types and environmental carrying capacity is essential for the continued development of Chinese industrialization and urbanization.Thus,utilizing a series of key indexes including the per-capita potential of available land resources,the per-capita potential of available water resources,the degree of environmental stress,and the degree of ecological restriction,a step-by-step,integrated measuring method is presented here to understand the constrained carrying elements of water and land resources as well as environment and ecology.Spatial differences are analyzed and area types classified at the county level across China.Results reveal that：（1）Almost 90%of China is strongly constrained by both resources and the environment,while nearly 50%of national territory is strongly constrained by two elements,especially in areas of intensive population and industry to the east of the Helan-Longmen Mountain line;（2）Densely populated areas of eastern and central China,as well as on the Tibetan Plateau,are strongly constrained by a shortage of land resources,while North China,the northwest,northeast,the Sichuan basin,and some southern cities are experiencing strong constraints because of water shortages.In contrast,the North China plain,the Yangtze River delta,northern Jiangsu,Sichuan province,Chongqing municipality,Guizhou and Guangxi provinces,the northeast plain,and the northern Loess Plateau are constrained by high levels of environmental stress.Areas of China that are strongly ecologically constrained tend to be concentrated to the southwest of the Tianshan-Dabie Mountain line,as well as in the northeast on the Loess Plateau,in the Alashan of Inner Mongolia,in northeast China,and in the northern Jiangsu coastal area;（3）Constraints on national resources and environmental carrying capacity are diverse and cross-cut China,meanwhile,multi-element spatial distribution does reveal a degree of relative centralization.With the exception of the Tibetan Plateau which is resources-ecological constraint,other areas subject to cross constraints are mainly concentrated to the east of the Helan-Longmen Mountain line.

Planning projects with scarce resources:Yesterday,today and tomorrow's research challenges

This paper is an invited request to describe the main research challenges in the domain of resourceconstrained project scheduling. The paper is split up in three parts. In today's challenges, research endeavors that have received a significant, but still not enough, attention have been described. In tomorrow's research challenges,some promising research avenues for future research have been given. Finally, in yesterday's challenge, a research topic that started decades ago, is said to have still a huge potential in tomorrow's research agenda. This paper does not intend to give a full literature overview, nor a summary of all possible research paths. Instead, it is inspired from the author's experience in academic research and practical consultancy and it serves as a personal opinion on a nonexhaustive set of promising research avenues, rather than giving a full literature-based advice for future research directions.

Resource-constrained Project Scheduling with Overlapping Activities Based on Extended Dependency Structure Matrix

Dependency Structure Matrix （DSM） is a successful and powerful tool for representing and analyzing dependencies between the items, but for external influencing factors it cannot charge effectively. This paper sets the stage for connecting the activities and resources, which not only considers information flow but also resources constrains.We first introduce the DSM to represent the degree of overlapping between the activities in a project. Then we present the Extended DSM combined former DSM and resource factors to calculate the project duration. Finally, the practical significance of the Extended DSM is confirmed by an illustrative example.

Modeling the impacts of drying trend scenarios on land systems in northern China using an integrated SD and CA model

Climate-induced drought has exerted obvious impacts on land systems in northern China.Although recent reports by the Intergovernmental Panel on Climate Change(IPCC) have suggested a high possibility of climate-induced drought in northern China,the potential impacts of such drying trends on land systems are still unclear.Land use models are powerful tools for assessing the impacts of future climate change.In this study,we first developed a land use scenario dynamic model(iLUSD) by integrating system dynamics and cellular automata.Then,we designed three drying trend scenarios(reversed drying trend,gradual drying trend,and acceleration of drying trend) for the next 25 years based on the IPCC emission scenarios and considering regional climatic predictions in northern China.Finally,the impacts of drying trend scenarios on the land system were simulated and compared.An accuracy assessment with historic data covering 2000 to 2005 indicated that the developed model is competent and reliable for understanding complex changes in the land use system.The results showed that water resources varied from 441.64 to 330.71 billion m3 among different drying trend scenarios,suggesting that future drying trends will have a significant influence on water resource and socioeconomic development.Under the pressures of climate change,water scarcity,and socioeconomic development,the ecotone(i.e.,transition zone between cropping area and nomadic area) in northern China will become increasingly vulnerable and hotspots for land-use change.Urban land and grassland would have the most prominent response to the drying trends.Urban land will expand around major metropolitan areas and the conflict between urban and cultivated land will become more severe.The results also show that previous ecological control measures adopted by the government in these areas will play an important role in rehabilitating the environment.In order to achieve a sustainable development in northern China,issues need to be addressed such as how to arrange land use structure and patterns rationally,and how to adapt to the pressures of climate change and socioeconomic development together.

Rough set based optimization method of machine tools in cloud manufacturing

Cloud Manufacturing(CMfg),combining with the technologies of Cloud computing and Internet of Things,is an intelligent networked manufacturing model,which can quickly integrate various distributed manufacturing resources for collaboratively completing the complex and customized manufacturing tasks.One of the key technologies supporting this model is the optimal manufacturing resources in the CMfg systems,typically machine tools(MTs).In this paper,the attributes of MTs in cloud environment are analyzed,the constraint relationship between the attributes and the optimization criteria of MTs is established,and an optimization method of MTs based on rough set is proposed.Finally,a case study is discussed to validate the feasibility and effectiveness of the proposed method.