A Planning Method for Operational Test of UAV Swarm Based on Mission Reliability

The unmanned aerial vehicle(UAV)swarm plays an increasingly important role in the modern battlefield,and the UAV swarm operational test is a vital means to validate the combat effectiveness of the UAV swarm.Due to the high cost and long duration of operational tests,it is essential to plan the test in advance.To solve the problem of planning UAV swarm operational test,this study considers the multi-stage feature of a UAV swarm mission,composed of launch,flight and combat stages,and proposes a method to find test plans that can maximize mission reliability.Therefore,a multi-stage mission reliability model for a UAV swarm is proposed to ensure successful implementation of the mission.A multi-objective integer optimization method that considers both mission reliability and cost is then formulated to obtain the optimal test plans.This study first constructs a mission reliability model for the UAV swarm in the combat stage.Then,the launch stage and flight stage are integrated to develop a complete PMS(Phased Mission Systems)reliability model.Finally,the Binary Decision Diagrams(BDD)and Multi Objective Quantum Particle Swarm Optimization(MOQPSO)methods are proposed to solve the model.The optimal plans considering both reliability and cost are obtained.The proposed model supports the planning of UAV swarm operational tests and represents a meaningful exploration of UAV swarm test planning.

Practical Strategies for Urban Rail Transit Loop Planning, Construction, and Operation

Urban rail transit loops are essential in urban rail transit systems and transportation networks.However,precise requirements and reference standards for rail transit loop design have yet to be established.There are certain areas for improvement in planning,construction,and operation.In the planning and design of urban rail transit loops,the scale of the city and the relationship between line operations should be considered to ensure that the line conforms to the city’s operating traffic conditions and can effectively cater to peak passenger flow requirements.This article presents strategies for planning,constructing,and operating urban rail transit loops,laying the foundation for the healthy operation of urban rail transit.

An Improved Iterated Greedy Algorithm for Solving Rescue Robot Path Planning Problem with Limited Survival Time

Effective path planning is crucial for mobile robots to quickly reach rescue destination and complete rescue tasks in a post-disaster scenario.In this study,we investigated the post-disaster rescue path planning problem and modeled this problem as a variant of the travel salesman problem(TSP)with life-strength constraints.To address this problem,we proposed an improved iterated greedy(IIG)algorithm.First,a push-forward insertion heuristic(PFIH)strategy was employed to generate a high-quality initial solution.Second,a greedy-based insertion strategy was designed and used in the destruction-construction stage to increase the algorithm’s exploration ability.Furthermore,three problem-specific swap operators were developed to improve the algorithm’s exploitation ability.Additionally,an improved simulated annealing(SA)strategy was used as an acceptance criterion to effectively prevent the algorithm from falling into local optima.To verify the effectiveness of the proposed algorithm,the Solomon dataset was extended to generate 27 instances for simulation.Finally,the proposed IIG was compared with five state-of-the-art algorithms.The parameter analysiswas conducted using the design of experiments(DOE)Taguchi method,and the effectiveness analysis of each component has been verified one by one.Simulation results indicate that IIGoutperforms the compared algorithms in terms of the number of rescue survivors and convergence speed,proving the effectiveness of the proposed algorithm.

A Novel Close-loop Strategy for Integrating Process Operations of Fluidized Catalytic Cracking Unit with Production Planning Optimization

Production planning models generated by common modeling systems do not involve constraints for process operations, and a solution optimized by these models is called a quasi-optimal plan. The quasi-optimal plan cannot be executed in practice some time for no corresponding operating conditions. In order to determine a practi- cally feasible optimal plan and corresponding operating conditions of fluidized catalytic cracking unit （FCCU）, a novel close-loop integrated strategy, including determination of a quasi-optimal plan, search of operating conditions of FCCU and revision of the production planning model, was proposed in this article. In the strategy, a generalized genetic algorithm （GA） coupled with a sequential process simulator of FCCU was applied to search operating conditions implementing the quasi-optimal plan of FCCU and output the optimal individual in the GA search as a final genetic individual. When no corresponding operating conditions were found, the final genetic individual based correction （FGIC） method was presented to revise the production planning model, and then a new quasi-optimal production plan was determined. The above steps were repeated until a practically feasible optimal plan and corresponding operating conditions of FCCU were obtained. The close-loop integrated strategy was validated by two cases, and it was indicated that the strategy was efficient in determining a practically executed optimal plan and corresponding operating conditions of FCCU.

Optimal Operation of Multipurpose Reservoir for Irrigation Planning with Conjunctive Use of Surface and Groundwater

In the present study, a Linear Programming (LP) model is developed for the conjunctive use of surface water and ground water to obtain the optimal operating policy for a multipurpose single reservoir. The objective of the present study is to maximize the net benefit from the command area under consideration. The constraints imposed on the objective function are maximum and minimum irrigation demands, reservoir storages and canal capacity. The model takes into account the continuity constraint which includes inflows in to the reservoir, releases for irrigation, releases for hydro-power generation, evaporation losses, feeder canal releases, initial and final storages in the reservoir in each time period. The developed model is applied to the case study of Jayakwadi reservoir stage-I, built across river Godavari, Maharashtra, India. Initially the model is solved for the availability of surface water which results in net benefit of 3373.45 million rupees with irrigation intensity is 57.07%. Next the model solved by considering the availability of surface water and available potential of groundwater in the area, which results in net benefits of 3590.02 million rupees with an intensity of irrigation 58.48%. The present model takes in to account the socio-economic requirement of growing the essential crops to meet the requirement of the society. The model has also generated the canal wise optimal releases for irrigation and power, monthly utilization of groundwater, storages in the reservoir at the end of every month and corresponding head over the turbine.

Remote Operation SW for USV: Part I. Integrated Mission Planning System

The integrated Mission Planning System?(MPS) of Unmanned Surface Vehicle?(USV) refers to the process which can recognize, decide, plan situations and carry out missions, such as human beings, for all incidental or complex events occurring at sea. In the actual operating environment, it is necessary to develop a simulation software environment and analyze, verify it in advance so as to make an appropriate mission plan considering equipment, sensor, fuel, and other available resources. The existing USV mission planning process methodology has several limitations in the analysis of USV missions because the scenario to be tested is limited and autonomy of USV is not considered sufficiently. To overcome these problems, we constructed a process that considers various missions and is more autonomous, and an integrated environment in which to experiment. In this study, we designed a multi-agent based USV Integrated Mission Planning System and modeled each component. In addition, we constructed the USV remote operation S/W based on M&S that user can experiment with the modeled process and verified the usefulness of the developed system through simulations.

Improved Optimal Operation Planning Method Based on Tabu Search for Residential PEFC-CGS Considering Ramping Rate

This paper proposes an improved optimal operation planning method for residential PEFC-CGS (Polymer Electrolyte Fuel CellCo-Generation System). Residential PEFC-CGS has recently been gathering attention as one of the distributed power sources with high efficiency and low environmental impacts. Previous research pointed out that the output variations of PEFC adversely affect the durability. It can be surmised that smaller output variations will be desired to extend durability years. However, in this field, ramping rate have not been sufficiently considered. For local search and tabu search, ramping rate constraint makes our operation planning difficult because it restricts the search for feasible neighborhood solutions. Therefore, the authors proposed a method to deal with typical and harsher ramping rate constraints in comparison with conventional methods. There are two key points for the improvement. One is the reinforcement of the search along the output power axis;the other is to make use of the strategy of tabu search which avoids the local optimal solutions. The simulation results show the effectiveness of the proposed method in the daily operation planning. Furthermore, in the case using typical ramping rate parameter, it is confirmed that tabu search doesn’t contribute the reduction of daily operational cost due to the above stated restriction of the search area.

Optimal Irrigation Planning and Operation of Multi Objective Reservoir Using Fuzzy Logic

In the present study the MOFLP models have been developed for the optimal cropping pattern planning which maximizes the four objectives such as Net Benefits (NB), Crop Production (CP), Employment Generation (EG) and Manure Utilization (MU) under conflicting situation and also, for maximization of Releases for Irrigation (RI) and Releases for Power (RP) simultaneously under uncertainty by considering the fuzziness in the objective functions. The developed models have been applied using the LINGO 13 (Language for Interactive General Optimization) optimization software to the case study of the Jayakwadi Project Stage-II across Sindhphana River, in the State of Maharashtra India. The various constraints have been taken into consideration like sowing area, affinity to crop, labour availability, manure availability, water availability for optimal cropping pattern planning. Similarly constraints to find the optimal reservoir operating policy are releases for power and turbine capacity, irrigation demand, reservoir storage capacity, reservoir storage continuity. The level of satisfaction for a compromised solution of optimal cropping pattern planning for four conflicting objectives under fuzzy environment is worked out to be λ = 0.68. The MOFLP compromised solution provides NB = 1088.46 (Million Rupees), CP = 241003 (Tons), EG = 23.13 (Million Man days) and MU = 111454.70 (Tons) respectively. The compromised solution for optimal operation of multi objective reservoir yields the level of satisfaction (λ) = 0.533 for maximizing the releases for irrigation and power simultaneously by satisfying the constraint of the system under consideration. The compromised solution provides the optimal releases, i.e. RI = 348.670 Mm3 and RP = 234.285 Mm3 respectively.

Proposal for a Project of Integration of IT Tools With Focus on Planning and Control of Operations on the Shop Floor

Manufacturing system, with high level of complexity and with a mix of semi-repetitive and repetitive products, to become productive, should seek the standardization of products and processes to obtain the optimization of use of production resources. However, it is necessary to measure the productivity, so that the system of measurement and control of manufacturing processes are an element critical as to ensure greater visibility of the flow＇s restrictions, minimized when detected properly. In this case, the automation of factory＇s measurement process can effectively contribute to ensuring the effectiveness of the function control of a manufacturing system. It is important to consider that the automation of the system of measurement and control of manufacturing processes, of complex environment, is heavily dependent of IT tools applied directly in the interface computational between the operation systems and the corporate systems. This heavy reliance, if exploited technically properly, allows that automation of the system of measurement and control of production makes the access to time real of availability of manufacturing process＇s data, such as processing time and setup time that it can export to a specialist software in programming production, for example, feasible. In this paper, the automation of the system of measurement and control of production is approached, in order to identify the main possibilities of the design of an information system capable to integrate the flow of information in an environment internal on manufacturing organizations, with emphasis in the digital manufacturing paradigm.

Minimum dose path planning for facility inspection based on the discrete Rao-combined ABC algorithm in radioactive environments with obstacles

Workers who conduct regular facility inspections in radioactive environments will inevitably be affected by radiation.Therefore,it is important to optimize the inspection path to ensure that workers are exposed to the least amount of radiation.This study proposes a discrete Rao-combined artificial bee colony(ABC)algorithm for planning inspection paths with minimum exposure doses in radioactive environments with obstacles.In this algorithm,retaining the framework of the traditional ABC algorithm,we applied the directional solution update rules of Rao algorithms at the employed bee stage and onlooker bee stage to increase the exploitation ability of the algorithm and implement discretion using the swap operator and swap sequence.To increase the randomness of solution generation,the chaos algorithm was used at the initialization stage.The K-opt operation technique was introduced at the scout bee stage to increase the exploration ability of the algorithm.For path planning in an environment with complex structural obstacles,an obstacle detour technique using a recursive algorithm was applied.To evaluate the performance of the proposed algorithm,we performed experimental simulations in three hypothetical environments and compared the results with those of improved particle swarm optimization,chaos particle swarm optimization,improved ant colony optimization,and discrete Rao’s algorithms.The experimental results show the high performance of the proposed discrete Rao-combined ABC algorithm and its obstacle detour capability.

SOMS: A Subway Operation and Maintenance System Based on Planned Maintenance Model with Train State

This paper aims to propose a modeling framework for subway operation and maintenance system (SOMS), which analyzes the train condition data based on both train sensor network data and basis train maintenance plan. The system is formulated into five function modules, and the research problem is to determine one auxiliary maintains plan, including the time allocation and frequency of maintenance. The case of Guangzhou metro is conducted to illustrate the applicability of SOMS, and the results reveal a number of interesting insights into subway maintenance system, i.e., the worksheet can reduce duplication of redundant maintenance work, the repair cost, and the damage caused by frequent disassembly.

Operations Improvement Function and Organisational Adaptability of Petroleum Tank Farms in South-South, Nigeria

The study examined the nexus between operations improvement function (dimensioned by contingency planning, benchmarking and continuous improvement processes) and organisational adaptability of Petroleum tank farms in South-South, Nigeria. The contingency theory and the theory of routine dynamics underpinned the study, and positivism was the underlying philosophy. The study adopted the cross-sectional survey through the use of questionnaire. 820 middle and top-level managers constituted the elements of the population, and the Krejcie & Morgan’s formula was used to determine the sample size of 262 respondents. Structural Equation Modeling was deployed to test the hypotheses at a 0.05 significance level. The results showed that contingency planning;benchmarking and continuous improvement processes all have a significant positive relationship with organisational adaptability of Petroleum tank farms in South-South, Nigeria. The study concludes that Petroleum tank farms’ operations should focus on the adoption of contingency planning, benchmarking and continuous improvement processes to enhance organisational adaptability. Therefore, it is recommended that the management of Petroleum tank farms should put in place mechanisms to advance continuous improvement processes by allocating the necessary amount of resources, such as energy, time and money, in order to promote the continuous development of the continuous improvement systems. Furthermore, managers of Petroleum tank farms should make better the adoption of contingency planning, ensuring that there is as much necessary training and information for employees on how to act during a crises situation, in order to evaluate safety and prepare in advance for recovery from disasters.

Optimization method of urban rail train operational plan based on O-D time-varying demand

Purpose–Under the constraints of given passenger service level and coupling travel demand with train departure time,this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.Design/methodology/approach–The authors optimize the train operational plan in a special network layout,i.e.an urban rail corridor with dead-end terminal yard,by decomposing it into two sub-problems:train timetable optimization and rolling stock circulation optimization.As for train timetable optimization,the authors propose a schedule-based passenger flow assignment method,construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm.For the optimization of rolling stock circulation,the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.Findings–The case study shows that the train operational plan developed by the study’s approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.Originality/value–The example verifies the efficiency of the model and algorithm.

Simulation and optimization approach for uncertainty-based short-term planning in open pit mines

Accuracy in predictions leads to better planning with a minimum of opportunity lost. In open pit mining,the complexity of operations, coupled with a highly uncertain and dynamic production environment,limit the accuracy of predictions and force a reactive planning approach to mitigate deviations from original plans. A simulation optimization framework/tool is presented in this paper to account for uncertainties in mining operations for robust short-term production planning and proactive decision making. This framework/tool uses a discrete event simulation model of mine operations, which interacts with a goalprogramming based mine operational optimization tool to develop an uncertainty based short-term schedule. Using scenario analysis, this framework allows the planner to make proactive decisions to achieve the mine's operational and long-term objectives. This paper details the development of simulation and optimization models and presents the implementation of the framework on an iron ore mine case study for verification through scenario analysis.

Operation optimization of the steel manufacturing process: A brief review

Against the realistic background of excess production capacity, product structure imbalance, and high material and energy consumption in steel enterprises, the implementation of operation optimization for the steel manufacturing process is essential to reduce the production cost, increase the production or energy efficiency, and improve production management. In this study, the operation optimization problem of the steel manufacturing process, which needed to go through a complex production organization from customers' orders to workshop production, was analyzed. The existing research on the operation optimization techniques, including process simulation, production planning, production scheduling, interface scheduling, and scheduling of auxiliary equipment, was reviewed. The literature review reveals that, although considerable research has been conducted to optimize the operation of steel production, these techniques are usually independent and unsystematic.Therefore, the future work related to operation optimization of the steel manufacturing process based on the integration of multi technologies and the intersection of multi disciplines were summarized.

Research on Flexible Transfer Line Schematic Design Using Hierarchical Process Planning

Flexible transfer line(FTL)is now widely used in ma ny manufacturing domains to realize efficiently,high quantity and economic prod uction.These manufacturing domains include automobile,tractor,internal-combu stion engine,and so on.In today’s competitive business environment,it is vit ally important for machine tool manufacturers to design flexible transfer line m ore effectively and efficiently according to a wider variety of customer demand s.This paper proposes an approach to a bidding-based flexible transfer line sc hematic design system.By analyzing manual FTL design process,the architecture o f flexible transfer line schematic design system(FTLSDS)is established.The syst em consists:of four processes:part feature modeling,process planning,FTL fac i lity layout and FTL evaluation. For FTL schematic design.a five-level proces s planning strategy named hierarchical process planning method is proposed.This method includes selection of manufacturing feature machining operation;part se t-up planning,feature sequencing,operation sequencing and process plan genera ting.The major decision relies on setup planning.According to the proceeding o f the hierarchical process planning,the structure of reasoning is proposed base d on blackboard.Under this paradigm,a cooperative effort between a hybrid coll ection of knowledge sources is possible.Total reasoning task can be divided int o some subtasks,and recursive-reasoning system is formed.It is convenient for process planning with step-by-step solution.Meanwhile,the blackboard is use d as the global data exchange area during all reasoning process.By using modula r technology,special purpose machine tools can be designed more efficiently and rapidly.The framework of machine modular design system to support machine requ irement design for FTL is established.By synthesizing the FTL evaluation criter ia.five evaluation criteria of flexible transfer 1ine schematic design are take n into account.An exampie is supplied to demonstrate and verify the validity an d feasibility of flexible transfer line schematic design approach.

Developing and Applying a Ship Operation Energy Efficiency Evaluation Index Using SEEMP: a Case Study of South Korea

The CO2 emission reduction policy of the International Maritime Organization(IMO)recommends that the operation of ships,managed by maritime transport companies,should be energy-efficient.An evaluation method that can determine how successfully a ship implements the energy efficiency plan is proposed in this study.To develop this method,the measures required for energy-efficient ship operations according to the Ship Energy Efficiency Management Plan(SEEMP)operational guidelines were selected.The weights of the selected measures,which indicate how they contribute to the energy-efficient operation of a ship,were derived using a survey based on the analytic hierarchy process(AHP)method.Consequently,using these measures and their weights,a new evaluation method was proposed.This evaluation method was applied to shipping companies in South Korea,and their ship operation energy efficiency indices were derived and compared.This evaluation method will be useful to the government and shipping companies in assessing the energy efficiency of ship operations.

Power system planning with high renewable energy penetration considering demand response

Electric system planning with high variable renewable energy(VRE)penetration levels has attracted great attention world-wide.Electricity production of VRE highly depends on the weather conditions and thus involves large variability,uncertainty,and low-capacity credit.This gives rise to significant challenges for power system planning.Currently,many solutions are proposed to address the issue of operational flexibility inadequacy,including flexibility retrofit of thermal units,inter-regional transmission,electricity energy storage,and demand response(DR).Evidently,the performance and the cost of various solutions are different.It is relevant to explore the optimal portfolio to satisfy the flexibility requirement for a renewable dominated system and the role of each flexibility source.In this study,the value of diverse DR flexibilities was examined and a stochastic investment planning model considering DR is proposed.Two types of DRs,namely interrupted DR and transferred DR,were modeled.Chronological load and renewable generation curves with 8760 hours within a whole year were reduced to 4 weekly scenarios to accelerate the optimization.Clustered unit commitment constraints for accommodating variability of renewables were incorporated.Case studies based on IEEE RTS-96 system are reported to demonstrate the effectiveness of the proposed method and the DR potential to avoid energy storage investment.

Current status of medical support in military operations other than war in domestic and overseas

Objective: To investigate the current status of medical support in military operations other than war (MOOTW) in domestic and overseas. Methods: This paper mainly adopts the descriptive, comparative and induction research methods. The current status of medical support in MOOTW in China, America, Russia, Israel, Canada, had been studied through some official papers, and series of professional books by analysis the precise date in various kinds of emergency event. Results: The contrast shows that there is still a quite huge development in medical support in MOOTW, no matter in China, or in other countries. Conclusion: In order to strengthen the forces, besides building professional rescue teams, it is necessary to take a regular revise of plans, according to missions` needs.