A mixed integer linear programming approach for municipal solid waste management

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Unmanned Aerial Vehicle Inspection Routing and Scheduling for Engineering Management

Technological advancements in unmanned aerial vehicles(UAVs)have revolutionized various industries,enabling the widespread adoption of UAV-based solutions.In engineering management,UAV-based inspection has emerged as a highly efficient method for identifying hidden risks in high-risk construction environments,surpassing traditional inspection techniques.Building on this foundation,this paper delves into the optimization of UAV inspection routing and scheduling,addressing the complexity introduced by factors such as no-fly zones,monitoring-interval time windows,and multiple monitoring rounds.To tackle this challenging problem,we propose a mixed-integer linear programming(MILP)model that optimizes inspection task assignments,monitoring sequence schedules,and charging decisions.The comprehensive consideration of these factors differentiates our problem from conventional vehicle routing problem(VRP),leading to a mathematically intractable model for commercial solvers in the case of large-scale instances.To overcome this limitation,we design a tailored variable neighborhood search(VNS)metaheuristic,customizing the algorithm to efficiently solve our model.Extensive numerical experiments are conducted to validate the efficacy of our proposed algorithm,demonstrating its scalability for both large-scale and real-scale instances.Sensitivity experiments and a case study based on an actual engineering project are also conducted,providing valuable insights for engineering managers to enhance inspection work efficiency.

Energy Management of Networked Smart Railway Stations Considering Regenerative Braking, Energy Storage System, and Photovoltaic Units

The networking of microgrids has received significant attention in the form of a smart grid.In this paper,a set of smart railway stations,which is assumed as microgrids,is connected together.It has been tried to manage the energy exchanged between the networked microgrids to reduce received energy from the utility grid.Also,the operational costs of stations under various conditions decrease by applying the proposed method.The smart railway stations are studied in the presence of photovoltaic(PV)units,energy storage systems(ESSs),and regenerative braking strategies.Studying regenerative braking is one of the essential contributions.Moreover,the stochastic behaviors of the ESS’s initial state of energy and the uncertainty of PV power generation are taken into account through a scenario-based method.The networked microgrid scheme of railway stations(based on coordinated operation and scheduling)and independent operation of railway stations are studied.The proposed method is applied to realistic case studies,including three stations of Line 3 of Tehran Urban and Suburban Railway Operation Company(TUSROC).The rolling stock is simulated in the MATLAB environment.Thus,the coordinated operation of networked microgrids and independent operation of railway stations are optimized in the GAMS environment utilizing mixed-integer linear programming(MILP).

Evaluating the Performance of Iranian Football Teams Utilizing Linear Programming

In this paper, we utilize Data Envelopment Analysis (DEA), which is a linear programming-based technique, for evaluating the performance of the teams which operate in the Iranian primer football league. We use Analytical Hierarchy Process (AHP) technique for aggregating the sub-factors which involve in input-output factors, and then DEA is used for calculating the efficiency measures. Also, AHP is used to construct some weight restrictions for increasing the discrimination power of the used DEA model. For calculating the efficiency measures, input-oriented weight-restricted BCC model is utilized.

Water Supply and Demand Sensitivities of Linear Programming Solutions to a Water Allocation Problem

This work formulates and implements a mathematical optimization program to assist water managers with water allocation and banking decisions to meet demands. Linear programming is used to formulate the constraints and objective function of the problem and tests of the developed program are performed with data from the Castaic Lake Water Agency (CLWA) in Southern California. The problem is formulated as a deterministic programming problem over a five year planning horizon with annual resolution. The program accepts annual water allocations from the State Water Project (SWP) in California. It then determines the least-cost feasible allocation of this water toward meeting annual demands in the five-year planning horizon. Local water sources, including water recycling, and water banking programs with their constraints and costs are considered to determine the optimal water allocation policy within the planning horizon. Although there is not enough information to fully account for the uncertainty in future allocations and demands as part of the decision problem solution for CLWA, uncertainty in the SWP allocation is considered in the tests, and sensitivity analyses is performed with respect to demand increases to derive inferences regarding the behavior of the median minimum-cost solutions and of the risk of failure to meet demand.

An Innovative Genetic Algorithms-Based Inexact Non-Linear Programming Problem Solving Method

In this paper, an innovative Genetic Algorithms (GA)-based inexact non-linear programming (GAINLP) problem solving approach has been proposed for solving non-linear programming optimization problems with inexact information (inexact non-linear operation programming). GAINLP was developed based on a GA-based inexact quadratic solving method. The Genetic Algorithm Solver of the Global Optimization Toolbox (GASGOT) developed by MATLABTM was adopted as the implementation environment of this study. GAINLP was applied to a municipality solid waste management case. The results from different scenarios indicated that the proposed GA-based heuristic optimization approach was able to generate a solution for a complicated nonlinear problem, which also involved uncertainty.

Sensor management based on fisher information gain

Multi-sensor system is becoming increasingly important in a variety of military and civilian applications. In general, single sensor system can only provide partial information about environment while multi-sensor system provides a synergistic effect, which improves the quality and availability of information. Data fusion techniques can effectively combine this environmental information from similar and/or dissimilar sensors. Sensor management, aiming at improving data fusion performance by controlling sensor behavior, plays an important role in a data fusion process. This paper presents a method using fisher information gain based sensor effectiveness metric for sensor assignment in multi-sensor and multi-target tracking applications. The fisher information gain is computed for every sensor-target pairing on each scan. The advantage for this metric over other ones is that the fisher information gain for the target obtained by multi-sensors is equal to the sum of ones obtained by the individual sensor, so standard transportation problem formulation can be used to solve this problem without importing the concept of pseudo sensor. The simulation results show the effectiveness of the method.

Discrete optimization models and methods for management systems of pavement maintenance and rehabilitation

With the rapid development of highway construction and formation of the highway network in China,the man- agement of pavement maintenance and rehabilitation （MR） activities has become important.In this paper,four discrete optimization models are proposed for different parties involved in the management system： government,highway agent,con- tractor and the common users.These four optimal decision models are formulated as linear integer programming problems with binary decision variables.The objective function and constraints are based on the pavement performance and prediction model using the pavement condition index （PCI）.Numerical experiments are carried out with the data from a highway system in Sichuan Province which show the feasibility and effectiveness of the proposed models.

Simplex of HR： Talent Management With Simplex Methodology

This study searches for use of simplex theory in talent management. It is a research topic belonging to this study. Human resource management （HRM） can be described with performance focus and talent management. This study presents a new perspective in talent management. Firstly, Talent management may be described with fulfilling organizational positions by bets talents, because talents further performance of departments and performance of firm. Firm has departments, such as production department, marketing departments, finance department, and etc.. This study suggests simplex method for talent management for practitioners. It identifies research question and has two propositions that simplex may be used in talent management. Secondly, study depicts linear of American HRM It is based on a relationship among human resource （HR） systems, various HRM practices, and organizational performance. Linear proposition of study is that, HRM practices as a system have an impact on firm performance （goal function）.

基于大数据的煤炭企业决策模型研究与应用

煤矿的安全生产运营离不开大数据的支持,为利用大数据分析技术和业务模型,给经营决策提供支持,从而实现效益最大化。文章结合当前大型煤炭能源企业在发展大数据方面所具有的信息化基础,探讨研究大数据在企业经营智能决策中的应用,根据国能BT煤炭部门实际生产经营数据,创建了生产优化模型、月度自产煤供应量及外购煤采购量计算模型和决策模型,并将模型部署至服务器,应用于煤矿WL和煤矿LJH,结果表明模型表现良好,并通过对煤矿实际数据的实证分析,验证了该模型的有效性。

考虑交叉口使用数量的救援交通优化研究

为科学规划局域突发灾害下救援车辆对道路的占用,通过考虑救援车辆在路网上通行时使用的交叉口数量,以救援车辆尽快到达受灾区域为目标,建立救援交通优化的混合整数线性规划模型。针对救援车辆使用的交叉口数量的约束值上限为未知参数且无约束进行限制的特点,设计两阶段算法,分析救援车辆在路网上通行时对交叉口的使用情况及其对路径选择与通行效率的影响,提出救援车辆路径选择的建议。结果表明:通过限制救援车辆在路网上通过的交叉口数量,能够在不延误救援车辆到达受灾区域的情况下,获得不同的最优救援路径并减少占用的道路。因此,调整救援车辆在路网上通过的交叉口数量可以用于优化路网资源配置。

Toward Optimal Periodic Crowd Tracking via Unmanned Aerial Vehicle

Crowd management and analysis(CMA)systems have gained a lot of interest in the vulgarization of unmanned aerial vehicles(UAVs)use.Crowd tracking using UAVs is among the most important services provided by a CMA.In this paper,we studied the periodic crowd-tracking(PCT)problem.It consists in usingUAVs to follow-up crowds,during the life-cycle of an open crowded area(OCA).Two criteria were considered for this purpose.The first is related to the CMA initial investment,while the second is to guarantee the quality of service(QoS).The existing works focus on very specified assumptions that are highly committed to CMAs applications context.This study outlined a new binary linear programming(BLP)model to optimally solve the PCT motivated by a real-world application study taking into consideration the high level of abstraction.To closely approach different real-world contexts,we carefully defined and investigated a set of parameters related to the OCA characteristics,behaviors,and theCMAinitial infrastructure investment(e.g.,UAVs,charging stations(CSs)).In order to periodically update theUAVs/crowds andUAVs/CSs assignments,the proposed BLP was integrated into a linear algorithm called PCTs solver.Our main objective was to study the PCT problem fromboth theoretical and numerical viewpoints.To prove the PCTs solver effectiveness,we generated a diversified set of PCTs instances with different scenarios for simulation purposes.The empirical results analysis enabled us to validate the BLPmodel and the PCTs solver,and to point out a set of new challenges for future research directions.

基于线性规划模型的制造业工艺成本协同管理——以造纸企业为例

基于工艺管理和成本管理理论,提出工艺成本的概念;在保证产品功能和质量的前提下,以生产要素的价格为自变量,以生产要素的供应量为限制条件,构建出工艺成本线性规划模型;同时,通过明确岗位职责和流程再造,促进跨部门协同,实现制造业在短期生产计划阶段降低产品成本的协同管理。造纸行业的应用结果表明,工艺成本协同管理能够降低产品成本(降幅约为2.69%~2.76%),促进跨部门协同,实现业财融合。

银行资产负债管理中资产分配模型

资产负债管理是商业银行的综合性管理技术 .分析了现有研究的特点和不足 ,以线性规划为手段 ,以资产收益最大化为目标函数 ,以法律约束、法规约束和经营管理约束为条件 ,在满足流动性、安全性和盈利性要求的前提下 ,建立了资产负债组合优化决策模型 。

分区达标控制法求解海域环境容量

提出可考虑二维扩散的分区达标控制法用于求解海域环境容量．引进贡献度系数将二维容量问题定义为线性规划问题，使各类水功能区在达到所对应的环境标准的前提下各排污口污染物允许排放量之和最大，并给出了用二维扩散模型计算贡献度系数的方法．将分区达标控制法应用于汕头市海域环境容量研究。

考虑需求侧管理的微网经济优化运行

建立了考虑需求侧管理的微网经济优化模型。将微网的电力负荷分为3个部分:固定负荷、可转移负荷、随机负荷,其中可转移负荷的管理是需求侧管理的主要内容,也是微网经济优化运行的重要目标。在分时电价的环境下,建立了微网中分布式电源与需求侧负荷优化管理的协调运行模型。通过函数线性化将该优化问题转化为一个混合整数规划问题,采用专业混合整数规划软件求解。仿真结果表明,考虑需求侧管理的微网经济运行相比不考虑时的总费用减少了3.83%,具有较好的经济效益。

道路工程土石方优化调配模型与工程应用

土石方优化调配是道路工程路基施工的重要问题。通过对土石方调配系统组成、调配关系的系统分析,在考虑开挖、填筑、借土区、弃土区、废料调配的前提下,以系统费用最低为目标,建立了道路工程土石方优化调配线性规划模型。同时,建立了土石方调配的坐标体系,用于计算调配关系中的运输距离,可以极大减少优化计算的数据需求量,增强模型的实用性。工程实践应用表明,本模型实现了对道路工程土石方调配的优化,可以提高开挖料的利用量,减少弃土和借土,最终实现调配系统费用最小化和道路沿线的环境保护。优化模型可以广泛应用于道路、堤防等工程的土石方调配问题中。

基于综合资源规划的供需资源优化组合模型

综合资源规划在电力规划中将需求侧资源与供应侧资源同时考虑,能够实现规划的总成本最小。在传统电力规划和相关研究成果的基础上提出一个将需求侧资源与供应侧资源同等纳入电力规划的线性规划模型,在模型中区分不同需求侧管理措施进行量化。该模型同时考虑了用电需求、系统可靠性、资源运行、资源可用性和污染物排放水平5类约束条件。通过算例验证了模型的有效性,与传统规划结果相比,应用该模型规划可实现系统总成本最低并减少污染的排放。

基于统一边际价格结算的用线性规划法消除阻塞的算法

针对统一边际价格结算的电力市场,提出了一种采用线性规划方法消除阻塞的数学模型。首先,形成阻塞支路的灵敏度矩阵,再乘以发电机的调整量等于过载支路的过载量负值,从而形成线性等式约束条件,然后根据各发电机的报价曲线形成虚拟发电机及其虚拟价格,最后以等价的系统调整费用增量最小为目标函数再加上其他约束条件构成了线性规划模型。对该模型进行求解,得出发电机的调整量。这种方法保证了快速的消除阻塞,减少了计算时间,同时也避免了逐条支路消除阻塞方法可能出现的振荡缺陷。通过IEEE-9节点系统和IEEE-30节点系统分析计算,验证了所提算法的正确性和有效性。

多目标规划在哈尔滨市地下水资源管理中的应用

建立了哈尔滨市地下水资源优化管理模型 ,将求解多目标最优化问题的约束法和线性加权法相结合 ,给出了一种综合解法 ,并将此法应用于所建立的水资源优化管理模型的求解。其结果可为该地区地下水资源的管理提供有参考价值的科学依据。