Delay Analysis under Multiple Baseline Updates

Windows delay analysis has been recognized as one of the most credible techniques for analyzing construction delays. To overcome some of the drawbacks of windows delay analysis, this paper introduces improvements to a computerized schedule analysis model so that it will produce accurate and repeatable results. The model considers multiple baseline updates due to changes in the durations of the activities and the logical relationships among them, as well as the impact of resource overallocation. The model uses a daily window size in order to consider all fluctuations in the critical path(s) and uses a legible representation of progress information to accurately apportion delays and accelerations among project parties. A simple case study has been implemented to demonstrate the accuracy and usefulness of the proposed delay analysis model. This research is useful for both researchers and practitioners and allows detailed and repeatable analysis of the progress of a construction project in order to facilitate corrective actions and claim analysis.     

Productivity Scheduling Method Compared to Linear and Repetitive Project Scheduling Methods

The analysis of project schedules is among the central tasks of construction managers. Parallel to the well-known critical path method, linear scheduling techniques have been researched. The two most fully developed existing methods, the linear scheduling model and the repetitive scheduling method, are reviewed. Based on a discussion of a published example, the new mathematical analysis method for linear and repetitive schedules is introduced. The productivity scheduling method is based on singularity functions that provide a flexible and powerful mathematical model for construction activities and their buffers that are characterized by their linear or repetitive nature. The steps of formulating initial equations, stacking and consolidating them, and deriving information about their criticality are described in detail. The mathematical approach of the new method allows an integrated treatment of activities regardless of the number of changes in productivity within them and does not depend on the graphical representation of the schedule.     

Permutation-Based Elitist Genetic Algorithm for Optimization of Large-Sized Resource-Constrained Project Scheduling

The resource-constrained project scheduling problem (RCPSP) has received the attention of many researchers because its general model can be used in a wide variety of construction planning and scheduling applications. The exact procedures and priority-rule-based heuristics fail to search for the optimum solution to the RCPSP of large-sized project networks in a reasonable amount of time for successful application in practice. This paper presents a permutation-based elitist genetic algorithm for solving the problem in order to fulfill the lack of an efficient optimal solution algorithm for project networks with 60 activities or more as well as to overcome the drawback of the exact solution approaches for large-sized project networks. The proposed algorithm employs the elitist strategy to preserve the best individual solution for the next generation so the improved solution can be obtained. A random number generator that provides and examines precedence feasible individuals is developed. A serial schedule generation scheme for the permutation-based decoding is applied to generate a feasible solution to the problem. Computational experiments using a set of standard test problems are presented to demonstrate the performance and accuracy of the proposed algorithm.     

一种基于多目标多约束的战时抢修力量调度

为合理调度抢修力量,快速修复受损装备,在对战场抢修中抢修力量调度问题进行分析的基础上,考虑抢修任务的时间约束、逻辑约束、抢修力量的平衡度约束、抢修力量的能力、抢修花费代价等约束,建立了使作战单元战斗力恢复最大,抢修花费代价最小的多目标优化模型。同时,给出了战时作战单元战斗力指数、抢修花费代价的计算方法,设计了相应遗传算法对模型优化求解。最后,以战场抢修任务为背景,用算例验证了模型的实用性和算法的有效性。     

面向IC生产模式的Job Shop调度问题的研究

针对即时定制生产模式的车间调度的特点,提出基于粒子群算法(PSO)的车间调度问题的解决方案.利用粒子群算法本身的优越性解决复杂的车间作业排序问题,克服了传统调度算法存在寻优效率低或全局寻优能力差的弱点.对粒子群的编码及寻优操作进行研究,确定了更适合车间调度问题的编码和操作方式,并将算法进行编程,应用到系统的车间调度部分.仿真结果表明,通过设置适当的参数,可以快速地得到理想的排序结果,能够适用于IC生产模式的车间调度问题.     

A novel precedence-based and heuristic approach for short-term scheduling of multipurpose batch plants

Many continuous-time formulations have been proposed during the last decades for short-term scheduling of multipurpose batch plants. Although these models establish advantages over discrete-time representations, they are still inefficient in solving moderate-size problems, such as maximization of profit in long horizon, and minimization of makespan. Unlike existing literature, this paper presents a new precedence-based mixed integer linear programming (MILP) formulation for short-term scheduling of multipurpose batch plants. In the new model, multipurpose batch plants are described with a modified state-task network (STN) approach, and binary variables express the assignments and sequences of batch processing and storing. To eliminate the drawback of precedence-based formulations which commonly include large numbers of batches, an iterative procedure is developed to determine the appropriate number of batch that leads to global optimal solution. Moreover, four heuristic rules are proposed to selectively prefix some binary variables to 0 or 1, thereby reducing the overall number of binary variables significantly. To evaluate model performance, our model and the best models reported in the literature (S&K model and I&F model) are utilized to solve several benchmark examples. The result comparison shows that our model is more effective to find better solution for complex problems when using heuristic rules. Note that our approach not only can handle unlimited intermediate storage efficiently as well as the I&F model, but also can solve scheduling problems in limited intermediate storage more quickly than the S&K model.     

An MILP approach for detailed scheduling of oil depots along a multi-product pipeline

Oil depots along products pipelines are important components of the pipeline transportation system and down-stream markets.The operating costs of oil depots account for a large proportion of the total system’s operating costs.Meanwhile,oil depots and pipelines form an entire system,and each operation in a single oil depot may have influence on others.It is a tough job to make a scheduling plan when considering the factors of delivering contaminated oil and batches migration.So far,studies simultaneously considering operating constraints and contaminated oil issues are rare.Aiming at making a scheduling plan with the lowest operating costs,the paper establishes a mixed-integer linear programming model,considering a sequence of operations,such as delivery, export, blending,fractionating and exchanging operations,and batch property differences of the same oil as well as influence of batch migration on contaminated volume.Moreover,the paper verifies the linear relationship between oil concentration and blending capability by mathematical deduction.Finally,the model is successfully applied to one of the product pipelines in China and proved to be practical.     

调度问题中的冲突研究

调度问题的本质是对存在的冲突进行消解的过程.针对调度问题,首先判断是否存在冲突;若可能存在冲突,再判断是否存在固有冲突;若不存在固有冲突,再进一步判断是否存在调度冲突或间接冲突.研究还涉及可能冲突任务紧集、可能冲突任务松集、冲突度等概念.其研究结果对调度算法设计有一定参考价值.     

An online approach to dynamic rescheduling for production planning applications

Manufacturing firms must often consider how to plan the production of a new order while containing the impact on the existing plan. Two approaches are typically used to solve the problem: online scheduling and rescheduling. State-of-the-art for both strategies is analyzed and methods available in the literature are proved to be inefficient for real world cases coming from production planning problems in a manufacturing firm. We propose an alternative approach combining the most effective aspects of both traditional approaches. The already available production plan and the characteristics of the new order to be planned are studied and used in order to generate a new production plan that meets two requirements: containing the number of changes to the existing plan and minimizing the delays due to the newly planned order. Constraint programming is used to implement the proposed approach. Results on case studies are also provided to evaluate the effectiveness of the proposed approach.     

An improved branch and bound procedure for scheduling a flow line manufacturing cell

This paper presents a new branch and bound procedure for scheduling a flow-line manufacturing cell. This procedure and an existing procedure are tested on several problem sets with varying numbers of families, jobs and machines, and varying setup time distributions. The results show that the new procedure solves small problems dramatically faster than the existing procedure. Three heuristic procedures, based on the new branch and bound procedure, are developed. These heuristic procedures as well as a tabu search procedure are tested on problem sets with larger problem sizes. The results show that one of the new procedures generates solutions with improved makespans compared to the tabu search procedure.