考虑时间和油耗的拖轮多目标优化调度研究

进出港口的大型船舶需向港口申请拖轮协助以进行靠离泊作业。拖轮调度是港口重要的计划事项之一。针对拖轮调度过程中需要平衡完工时间和油耗量以提高港口服务水平和降低拖轮公司经营成本的问题，本文以最小化拖轮最大完工时间和最小化拖轮总油耗量为目标，构建了混合整数规划拖轮多目标优化调度模型。模型还考虑了潮汐港口大量船舶在潮水期间集中进出港的特点，并根据拖轮在调度过程中的不同状态分类计量其产生的油耗量，以使模型更接近实际状况。为求解模型，运用了带有精英策略的非支配排序遗传算法(NSGA-II),算法采用一维实数编码，以事件建模思想设置适应度函数，并结合拖轮调度特点设计了遗传算子，求得的Pareto前沿解和算法对比验证了该算法的有效性。最后，以广州港港口拖轮调度实际运作数据作为算例，验证了模型的可行性与有效性，为港口拖轮调度计划提供了决策依据。     

基于遗传算子粒子群算法的拖轮动态调度

随着中国港口的发展,进出港口的船舶日益增多,使用拖轮的艘次逐渐增加.而当前极大部分港口所采用的基于人工经验的拖轮调度方案已难以保证船舶的顺利进出港口.如何根据复杂多变的进出港情况来制定合理的拖轮调度方案,已成为当前众多港口迫切需要解决的问题之一.通过分析港口拖轮作业过程与特点,建立了拖轮动态调度的数学模型,采用了基于动态遗传算子的改进粒子群优化算法对该模型进行求解.案例分析表明该拖轮动态调度模型是有效的.通过和传统粒子群算法对比分析,基于遗传算子的粒子群算法不仅在收敛速度上有明显的提高,而且求得的解更优.为港口拖轮动态调度的科学决策提供了依据.     

考虑路径冲突的AGV配置与调度优化

合理调度有限的码头资源以满足船舶的装卸时间要求是自动化集装箱码头的重要目标之一。针对自动化集装箱码头自动导引车(automated guided vehicle,AGV)配置与调度问题,考虑船舶装卸时间要求和AGV运输过程中的路径冲突,提出分阶段调度策略。将船舶装卸作业分为卸船阶段、装卸同步阶段、装船阶段三个阶段,在每个阶段中,建立以最小化最大完工时间和最小化AGV空载和等待时间为双目标的调度优化模型,并设计基于NSGA-Ⅱ的启发式算法求解。根据本阶段的实际完工时间,从最优解集中选择下一阶段AGV的配置与调度方案。最后对比其他调度方案表明本文调度方案能够满足集装箱船的装卸时间要求,且提高了AGV的利用率,更符合码头实际作业要求。     

建筑废料现场分拣协调调度优化研究

工程项目施工现场废料分拣的效率对施工进度具有重要的影响。通过分析现场废料分拣实施过程,建立了带有限中间缓冲的混合流水车间调度模型。提出了收集阶段作业排序的动态自适应算法和后续设备分配问题的考虑缓冲区的设备分配规则,在此基础上设计了废料分拣模型的启发式算法,平衡各分区工作量,进一步搜索最优解,并推导了问题的一个低界。实验结果表明,所提出算法能很好地对施工现场废料分拣问题进行求解,具有良好的收敛性和较高的时间效率。     

变邻域搜索分布估计算法求解舰载机保障作业调度问题

针对多资源、多约束的资源受限舰载机保障作业调度问题,提出了一种求解该问题的基于变邻域搜索的分布估计算法.首先,建立了考虑站位、设备、作业的优先级和安全性等约束的调度模型,该模型以舰载机保障作业的总完成时间和舰载机移动次数的加权和最小化为目标;其次,结合问题特征分析,提出了最早可用设备规则,对偶站位交换规则等两类启发式规则,定义了基于序置换排列的解的编码方式;再次,提出了分布估计算法(EDA)的概率分布更新模型,以及基于工序插入、交换、反转等邻域操作的变邻域搜索策略,设计了基于变邻域搜索的分布估计算法(EDAVNS);最后,基于单波次8架舰载机保障的仿真结果,验证了所提模型对舰载机保障作业调度问题具有较好的实用性.同时,基于5个不同规模的问题集的分析结果表明:与分布估计算法、变邻域搜索、遗传算法、以及只使用插入、交换、反转等单一邻域操作的EDA算法相比,EDAVNS均取得了最优的结果,验证了EDAVNS能有效地求解该问题,并较好地平衡全局探索与局部搜索.     

带有外包考虑的两阶段流水车间生产调度优化问题

将外包引入传统的生产调度优化问题,针对包括自产车间和外包车间在内的两阶段流水车间,考虑自产车间的定修、外包基于批次的运输以及外包车间的变动加工成本等因素,以最小化自产/外包总工期与最小化总成本为目标,构建混合整数非线性规划模型,解决包括加工任务分派、自产与外包各自的加工次序在内的生产调度优化问题。鉴于其属于NP-hard问题,设计了基于规则的启发式算法求解。最后运用数值实验验证了算法的有效性,并从运作管理的视角分析外包资源对生产系统的影响,进而对带有外包的调度优化策略与主要参数进行了敏感性分析。     

基于两阶段混合动态规划算法的龙门吊路径优化

产业界已出现利用多台轨道式龙门吊同时作业以提升集装箱码头装船效率的情况,由于需要确定每台龙门吊的取箱作业集合以及增加了“避免碰撞”、“顺次移动”等现实约束,故其移动路径规划问题在模型建立与求解上比单台轨道式龙门吊更为复杂。本文针对两台轨道式龙门吊同时作业的情形,建立了龙门吊移动路径网络模型,并开发了基于贪婪算法与动态规划的两阶段混合算法,并通过仿真算例,借助与基于实际调度规则所得到的调度方案的对比,验证了模型及优化算法的有效性与实用性。     

基于实际路网情境的配送车辆调度优化

在实际路网情境下结合车道数、车道宽度、路口信号灯设置等路网物理特性,构建了考虑综合交通阻抗的多车型车辆调度模型,提出了两阶段求解策略:第1阶段设计了改进A-star精确解算法用于计算客户时间距离矩阵;第2阶段针对实际路网的特征设计了混合模拟退火算法求解调度方案。以大连市某配送中心运营实例进行路网情境仿真试验,结果表明:改进A-star算法较改进Dijkstra算法具有更短的路径搜索时间;混合模拟退火算法求解结果较实际调度方案优化了13.1% 的综合成本;路网增流、区域拥堵和路段禁行三类路网情境均能对配送方案的车辆配置、路径选择、客户服务次序、作业时间和违约费用等5方面内容产生干扰,调度计划的制定需要详细考虑这些因素的变化。     

考虑任务优先约束的同类岸桥作业调度优化

分析了以箱组为任务对象QCSP与以整贝为任务对象QCSP的异同,指出前者更能均衡各岸桥作业负荷,并减少船舶装卸作业时间。考虑到岸桥具有作业效率差异的特点,将其视为同类平行机调度问题,同时结合任务优先约束、岸桥作业不可相互穿越与安全距离等特有约束,建立了更加符合实际的以箱组为任务对象的岸桥作业调度混合整数规划模型,其优化目标是最小化装卸作业的makespan。针对模型求解的复杂度,设计了一种遗传算法,对算法搜索空间进行了讨论,并推导了问题的低界。实验算例表明所建立的模型能够反映岸桥作业调度过程中作业效率差异及任务优先约束现象,其算法能够在允许的运算时间内获得稳定的满意解,并且优化结果要全面优于以整贝为任务对象QCSP的调度方案。     

基于贪婪禁忌搜索算法的垂岸式堆场出口箱装船翻箱研究

基于垂岸式自动化集装箱码头不同装船周期出口集装箱堆场多贝位混合堆存、场桥大车在贝位间频繁移动取箱装船特点,考虑装船发箱时场桥移动等操作时间及翻箱取箱次数对出口箱装船效率和连续性影响,建立多贝位出口箱装船堆场翻箱模型,提出两阶段贪婪禁忌搜索算法,将翻箱规则嵌入算法中,有效限制算法时间和解空间增长速度。通过算例,将提出的翻箱规则与现有常见翻箱规则进行对比,验证模型及算法的有效性与实用性。结果表明,提出的模型和算法可以在合理的求解时间内输出较优的翻箱方案,减少装船时场桥发箱作业时间,提高装船作业效率。     

Bicriteria train scheduling for high-speed passenger railroad planning applications

This paper is concerned with a double-track train scheduling problem for planning applications with multiple objectives. Focusing on a high-speed passenger rail line in an existing network, the problem is to minimize both (1) the expected waiting times for high-speed trains and (2) the total travel times of high-speed and medium-speed trains. By applying two practical priority rules, the problem with the second criterion is decomposed and formulated as a series of multi-mode resource constrained project scheduling problems in order to explicitly model acceleration and deceleration times. A branch-and-bound algorithm with effective dominance rules is developed to generate Pareto solutions for the bicriteria scheduling problem, and a beam search algorithm with utility evaluation rules is used to construct a representative set of non-dominated solutions. A case study based on Beijing–Shanghai high-speed railroad in China illustrates the methodology and compares the performance of the proposed algorithms.     

基于倒箱移动路径的集装箱堆场提箱作业优化模型

集装箱堆场提箱作业优化的目标是通过对倒箱搬运过程的优化使总作业成本最小。本文分析了正面吊设备的提箱作业过程,对作业规则和约束建立数学模型,在分析倒箱移动路径的基础上,提出了提箱作业优化模型。该模型为两层嵌套的组合优化模型,外层子模型针对提箱订单实现倒箱策略优化;内层子模型针对每一步倒箱作业寻找使倒箱作业成本最小的移动路径。提出了求解该模型的算法流程。最后,通过数值算例验证了优化模型的有效性。与传统人工作业方式的比较结果表明:本优化模型能够明显降低提箱作业成本。     

Analysis and control of maritime transit traffic through the İstanbul Channel: a simulation approach

This study involves a functional simulation model for the maritime transit traffic in the İstanbul Channel that investigates the Channel Traffic Rules and Regulations, vessel types, cargo characteristics, meteorological and geographical conditions, pilotage and tugboat services. The simulation model mainly focuses on the transit traffic in the Channel. This study provides a platform to analyze the effects of factors such as Rules and Regulations, number of tugboats and pilots, vessel type, traffic density and meteorological conditions on the maritime traffic in the Channels. Results obtained and reported in the study clearly indicate some interesting relationships among these factors. As the effect of five factors on eight responses are examined, the most significant factor is determined as number of pilots and tugboats in the service, while the second effective factor is the arrival rate of vessels.     

A heuristic solution framework for the resource constrained (multi-)project scheduling problem with sequence-dependent transfer times

We consider the problem of scheduling multiple projects subject to joint resource constraints. Most approaches proposed in the literature so far are based on the unrealistic assumption that resources can be transferred from one project to the other without any expense in time or cost. In order to contribute to closing this gap to reality, we generalise the multi-project scheduling problem by additionally including sequence- and resource-dependent transfer times, which represent setup activities necessary when a resource is removed from one project and reassigned to another (or from one job to another within the same project). In this paper, we define the modified resource constrained multi-project scheduling problem with transfer times (called RCMPSPTT), which aims at minimising the multi-project duration for the single-project approach or the mean project duration for the multi-project approach. We formulate both perspectives as an integer linear program, propose priority rule based solution procedures and present results of comprehensive computational experiments. Provided that the combination of scheduling scheme and priority rules is chosen appropriately, the procedures obtain good results. In particular, resource oriented priority rules are identified to be successful.     

A tabu-search heuristic for the flexible-resource flow shop scheduling problem

This paper presents a tabu-search heuristic for the flexible-resource flow shop scheduling (FRFS) problem [7]. The FRFS problem generalizes the classic flow shop scheduling problem by allowing job-operation processing times to depend on the amount of resource assigned to an operation; the objective is to determine simultaneously the job sequence, resource-allocation policy, and operation start times that optimize system performance. The tabu-search heuristic (TSH) employs a nested-search strategy based on a decomposition of the FRFS problem into these three components. We discuss computational experience with the THS procedure on more than 1600 test problems. The results show that TSH is effective in obtaining near-optimal solutions to the FRFS test problems. In particular, TSH generates optimal solutions for more than 70% of the test problems for which optimal solutions are known; overall, these solutions are within 0.3% of optimality on the average, and within 2.5% of optimality in the worst case.This research was supported in part by National Science Foundation grant SES90-22940.     

考虑机器调整次数和产品质量的卷烟批量计划和柔性流水车间调度集成问题

针对卷烟企业生产中的批量计划和柔性流水车间调度集成问题,构建了整数规划模型,目标函数由卷烟生产时间、生产线调整次数、卷烟质量、库存成本四部分组成。鉴于该问题的NP-hard性,设计遗传算法进行求解,通过合理设计遗传算子,避免不可行解出现。应用某卷烟企业数据得到优化排产结果,与该企业之前依照经验排产方案进行对比,发现优化排程结果在减少品牌转换次数,提高生产的连续性方面具有明显优势。该算法已作为某卷烟企业排产人员的排产参考,应用于排产决策中,取得了良好的效果,对卷烟企业制定排产计划具有一定的实际指导意义。     

A new approach to solving the multiple traveling salesperson problem using genetic algorithms

The multiple traveling salesperson problem (MTSP) involves scheduling m > 1 salespersons to visit a set of n > m locations so that each location is visited exactly once while minimizing the total (or maximum) distance traveled by the salespersons. The MTSP is similar to the notoriously difficult traveling salesperson problem (TSP) with the added complication that each location may be visited by any one of the salespersons. Previous studies investigated solving the MTSP with genetic algorithms (GAs) using standard TSP chromosomes and operators. This paper proposes a new GA chromosome and related operators for the MTSP and compares the theoretical properties and computational performance of the proposed technique to previous work. Computational testing shows the new approach results in a smaller search space and, in many cases, produces better solutions than previous techniques.     

Scheduling multi-stage parallel-processor services to minimize average response time

The problem of scheduling on a multi-stage parallel-processor architecture in computer centres is addressed with the objective of minimizing average completion time of a set of requests. The problem is modelled as a flexible flowshop problem for which few heuristics exist in the flowshop scheduling literature. A new three-phase heuristic is proposed in this paper. An extensive computational experiment has been conducted to compare the performance of the existing heuristics and the proposed heuristic. The results indicate that the proposed heuristic significantly outperforms the existing ones. More specifically, the overall average error of the best existing heuristic is about five times that of the proposed heuristic while the overall average CPU time of the proposed heuristic is about half of the best existing one. More importantly, as the number of requests increases, the CPU time of the proposed heuristic decreases considerably (compared to the best existing heuristic) while the ratio of the error (of the best existing to the proposed heuristic) of about five times remains almost the same.     

Integrated machine scheduling and vehicle routing with time windows

This paper integrates production and outbound distribution scheduling in order to minimize total tardiness. The overall problem consists of two subproblems. The first addresses scheduling a set of jobs on parallel machines with machine-dependent ready times. The second focusses on the delivery of completed jobs with a fleet of vehicles which may differ in their loading capacities and ready times. Job-dependent processing times, delivery time windows, service times, and destinations are taken into account. A genetic algorithm approach is introduced to solve the integrated problem as a whole. Two main questions are examined. Are the results of integrating machine scheduling and vehicle routing significantly better than those of classic decomposition approaches which break down the overall problem, solve the two subproblems successively, and merge the subsolutions to form a solution to the overall problem? And if so, is it possible to capitalize on these potentials despite the complexity of the integrated problem? Both questions are tackled by means of a numerical study. The genetic algorithm outperforms the classic decomposition approaches in case of small-size instances and is able to generate relatively good solutions for instances with up to 50 jobs, 5 machines, and 10 vehicles.     

服务大规模定制模式下的供应链调度优化

为了提升服务大规模定制(SMC)模式下供应链系统的运作柔性,应对客户较强的多样化需求特征,本文在对服务定制特征分析、服务阶段界定以及服务规模效应探讨的基础上,指出SCM模式下的供应链调度问题是一个典型的随机需求与随机资源约束的多目标动态优化问题。研究了SMC模式下供应链调度的优化目标与约束条件,建立了完整的随机多目标动态调度优化数学模型。基于SMC运作的特点,运用改进的蚁群算法对调度问题进行了求解。最后,通过实例分析了模型及算法的可行性、有效性及适用性。