Knowledge-Enabled Decision Support System for Routing Urban Utilities

This paper presents a Web-based system for supporting the selection of the most suitable routes for buried urban utilities. The aim of the proposed system is to support (not make) decisions through a collaborative semiautomated environment, in which stakeholders can share information and/or study the impacts of different routing alternatives with respect to decision constraints. First, the knowledge relating to route selection for urban utilities is represented through an ontology. The ontology defines the types and attributes of infrastructure products and the surrounding areas. It also defines the impacts of routing options on surrounding areas through a set of decision criteria adopted to evaluate the effectiveness of any route in terms of its potential impacts. A set of constraints are also defined to help represent/study the decision criteria. Second, a GIS-based system has been created to help visualize route data, interact with users, and support the needed discussions among stakeholders. The portal also achieves data interoperability through wrapping existing geospatial data with ontology structures. Finally, a set of reasoners have been created to help quantify/augment some of the constraints. The system is capable of (1)?extracting the attributes of each routing option, (2)?testing the interaction/conflicts between route attributes and the constraints of the surrounding area, (3)?studying the impacts of a route as stipulated in the ontology, (4)?referring users to existing best practices to help enhance routes or address conflicts and, when needed, (5)?develop objective measures for comparing different routes. On the microlevel (street level), route options are evaluated through a “constraint-satisfaction” approach. On the macrolevel (city level), route options are evaluated through a fuzzy inference scoring system. The proposed system focuses on facility life cycle, sustainability, and community impacts. Construction costing, scheduling, labor, and equipment along with other management issues can either be added to the system or, better, analyzed through integrating the system with four-dimensional (4D) modeling tools.     

Challenges in Line-of-Balance Scheduling

The line-of-balance (LOB) method of scheduling is well suited to projects that are composed of activities of a linear and repetitive nature. The objective of this study is to set down the basic principles that can be used in the development of a computerized LOB scheduling system that overcomes the problems associated with existing systems and creates solutions to problems encountered in the implementation of repetitive-unit construction. The challenges associated with LOB scheduling include developing an algorithm that handles project acceleration efficiently and accurately, recognizing time and space dependencies, calculating LOB quantities, dealing with resource and milestone constraints, incorporating the occasional nonlinear and discrete activities, defining a radically new concept of criticalness, including the effect of the learning curve, developing an optimal strategy to reduce project duration by increasing the rate of production of selected activities, performing cost optimization, and improving the visual presentation of LOB diagrams.     

Fuzzy Optimal Model for Resource-Constrained Construction Scheduling

Activity duration is uncertain due to the variation in the outside environment, such as weather, site congestion, productivity level, etc. Furthermore, resources for construction activities are limited in the real construction world so that scheduling must include resource allocation. A new optimal resource-constrained construction scheduling model is proposed in this paper, in which the effects of both uncertain activity duration and resource constraints are taken into account. Fuzzy set theory is used to model the uncertainties of activity duration. A genetic algorithm-based searching technique is adopted to search for the fuzzy optimal project duration under resource constraints. The model can effectively provide the optimal fuzzy profiles of project duration and resource amounts under the constraint of limited resources.     

Critical Space Analysis

The construction space scheduling problem has received relatively little attention from researchers and practitioners. We now have sophisticated methods of planning and analyzing the sequence of tasks within the work breakdown structure through time, but the problem of planning where on site those tasks are to be executed is not well-supported especially as those spaces are dynamic as the project progresses. We know that congestion on site reduces output and generates hazards, yet construction planners presently have to rely upon experience and intuition. The research reported here presents a decision support tool for construction project planners to help them address the space scheduling problem. After a review of recent developments in construction space scheduling, the concept of critical space analysis is presented. This forms the basis of decision support tools presented for marking up available space, allocating tasks to spaces, and analyzing and optimizing space loading in relation to the critical path—what we call space-time broking. Requirements capture and evaluation reports from construction planners suggest that the tools presented here have immediate practical relevance. The paper will, therefore, be of interest to both practitioners and researchers.     

Model based scheduling of a continuous annealing furnace

Abstract

The operational complexities and process constraints of an industrial continuous annealing operation invariably lead to empirically designed process cycles as well as manual scheduling practices. This methodology often results in suboptimal and inefficient operations. An integrated approach is presented here for maximising the productivity of a continuous furnace, where bundles of steel rods are annealed. For this purpose, a scheduling algorithm is proposed, which is coupled with a process model. The phenomenological process model is based on heat transfer and annealing kinetics. The scheduling algorithm is formulated to analyse the continuous annealing furnace under different operating conditions. The advantage of coupling the scheduling algorithm to the process model in enhancing productivity has been illustrated. Furthermore, it is shown that optimising the bundle diameter at a constant hearth speed is favourable for frequent dispatches of the product, whereas for less frequent dispatches, it is more efficient to vary the hearth speed.     

Critical Path Scheduling under Resource Calendar Constraints

Resource calendars specify nonworking days of driving resources involved in construction projects. As part of the resource availability constraints in critical path method (CPM) scheduling, resource calendars may postpone activity start time, extend activity duration, and hence prolong the total project duration. Ultimately, resource calendars bring about changes to the critical path identification. Research has yet to address how to incorporate the effects of multiple resource calendars on the total float determination. In this research, the popular P3 software is used as a tool for investigating the current practice of CPM scheduling under resource limit and calendar constraints. We assess P3’s advanced resource scheduling functions (including resource leveling and resource calendars) and identify P3’s potential errors in total float determination. Further, we propose a new method based on the forward pass analysis alone for accurately evaluating activity total float subject to resource calendar constraints. The application of the new method is illustrated with an activity-on-node case and a precedence-diagram-method case, with the results compared against those produced from P3. Our research has elucidated on some critical issues of resource-constrained scheduling in the application domain of construction project management. The findings will provide useful input for the vendors and users of the CPM software—which is not limited to P3—to improve the scheduling methodology as well as the accuracy of the resulting project schedules.     

Constraint-Based Planning with Integrated Production Scheduler over Internet

Identifying and removing constraints from bottleneck activities help to reduce uncertainties in construction processes and increases the transparency of project management. The present means of look-ahead planning do poorly in resolving hidden constraints in the supply chain and information flow. Accordingly, work plans are vulnerable to the uncertainties that result in flow variation. It has been realized that reducing and eliminating critical constraints through better means of look-ahead planning are the keys to achieving reliable workflow and, consequently, increased productivity. This paper presents a constraint-based planning tool, Integrated Production Scheduler (IPS), to enhance planning reliability while adopting lean construction principles and the theory of constraints. Unlike the critical path method, the IPS models two additional types of constraints related to resource supply and information exchange. It employs four activity buffers: working, shielding, pulling, and screening for managing critical constraints and shielding the production from uncertainties. The implementation of the IPS is prototyped as a distributed scheduling system using Internet technologies such as Java and XML. It facilitates setting up a transparent project management environment where faster communication and active collaboration among project members are achievable.     

Efficient Repetitive Scheduling for High-Rise Construction

A new scheduling and cost optimization model for high-rise construction is presented in this paper. The model has been formulated with a unique representation of the activities that form the building’s structural core, which need to be dealt with carefully to avoid scheduling errors. In addition, the model has been formulated incorporating: (1) the logical relationships within each floor and among floors of varying sizes; (2) work continuity and crew synchronization; (3) optional estimates and seasonal productivity factors; (4) prespecified deadline, work interruptions, and resource constraints; and (5) a genetic algorithms-based cost optimization that determines the combination of construction methods, number of crews, and work interruptions that meet schedule constraints. A computer prototype was then developed to demonstrate the model’s usefulness on a case study high-rise project. The model is useful to both researchers and practitioners as it better suits the environment of high-rise construction, avoids scheduling errors, optimizes cost, and provides a legible presentation of resource assignments and progress data.     

Non-Unit-Based Planning and Scheduling of Repetitive Construction Projects

Repetitive scheduling methods are more effective than traditional critical path methods in the planning and scheduling of repetitive construction projects. Nevertheless, almost all the repetitive scheduling methods developed so far have been based on the premise that a repetitive project is comprised of many identical production units. In this research a non-unit-based algorithm for the planning and scheduling of repetitive projects is developed. Instead of repetitive production units, repetitive or similar activity groups are identified and employed for scheduling. The algorithm takes into consideration: (1) the logical relationship of activity groups in a repetitive project; (2) the usage of various resource crews in an activity group; (3) the maintaining of resource continuity; and (4) the time and cost for the routing of resource crews. A sample case study and a case study of a sewer system project are conducted to validate the algorithm, as well as to demonstrate its application. Results and findings are reported.     

REILP Approach for Uncertainty-Based Decision Making in Civil Engineering

The civil and environmental decision-making processes are plagued with uncertain, vague, and incomplete information. Interval linear programming (ILP) is a widely applied mathematical programming method in assisting civil and environmental decision making under uncertainty. However, the existing ILP decision approach is found to be ineffective in generating operational schemes for practical decision support due to a lack of linkage between decision risk and system return. In addition, the interpretation of the ILP solutions represented as the lower and upper bounds of decision variables can cause problems of infeasibility and nonoptimality in the resulted implementation schemes. This study proposed a risk explicit ILP (REILP) approach to overcome the limitations of existing ILP approaches. The REILP explicitly reflects the tradeoffs between risk and system return for a decision-making problem under an interval-type uncertainty environment. A risk function was defined to enable finding solutions which maximize system return while minimizing system risk, hence leading to crisp solutions that are feasible and optimal for practical decision making. A numerical experiment on land-use decision making under total maximum daily load was conducted to illustrate the REILP approach. The model results show that the REILP approach is able to efficiently explore the interval uncertainty space and generate an optimal decision front that directly reflects the tradeoff between decision risks and system return, allowing decision makers to make effective decision based on the risk-reward information generated by the REILP modeling analysis.     

Optimum Design and Management of Pressurized Branched Irrigation Networks

The scarcity of water resources is the driving force behind modernizing irrigation systems in order to guarantee equal rights to all beneficiaries and to save water. Traditional distribution systems have the common shortcoming that water must be distributed through some rotational criteria. This type of distribution is necessary to spread the benefits of scarce resources. Irrigation systems based on on-demand delivery scheduling offer flexibility to farmers and greater potential profit than other types of irrigation schedules. However, in this type of irrigation system, the network design has to be adequate for delivering the demand during the peak period whilst satisfying minimum pressure constraints along with minimum and maximum velocity constraints at the farm delivery points (hydrants) and in the pipes, respectively. In this paper, optimum design and management of pressurized irrigation systems are considered to be based on rotation and on-demand delivery scheduling using a genetic algorithm. Comparison is made between the two scheduling techniques by application to two real irrigation systems. Performance criteria are formulated for the optimum design of a new irrigation system and better management of an existing irrigation system. The design and management problems are highly constrained optimization problems. Special operators are developed for handling the large number of constraints in the representation and fitness evaluation stages of the genetic algorithm. The performance of the developed genetic algorithm is assessed in comparison to traditional optimization techniques. It is shown that the methodology developed performs better than the linear programming method and that solutions generated by the modified genetic algorithm show an improvement in capital cost. The method is also shown to perform better in satisfying the constraints. Comparison between on-demand and rotation delivery scheduling shows that a greater than 50% saving can be achieved in total cost at the cost of reducing flexibility in the irrigation time. Finally, it is shown that minimizing standard deviation of flow in pipes does not result in the best distribution, and therefore minimum cost, neither for systems with uniform flows or those with large variations in discharge at hydrants.     

无人驾驶车辆路径跟踪控制研究现状

近年来路径跟踪控制的发展十分迅猛,研究者们发表了大量的研究成果。考虑到在相同或相近工况下的路径跟踪控制存在一些共性的技术问题与解决思路,从低速路径跟踪控制和高速路径跟踪控制两个角度对近年来的研究成果进行了回顾。在关于低速路径跟踪控制的研究工作中,研究者们较为重视前轮转角速度约束等系统约束对路径跟踪精确性的影响。目前减少系统约束影响的方法包括在规划参考路径时将系统约束纳入考虑,采用预瞄控制使控制器提前响应,以及采用线性模型预测控制（LMPC）或非线性模型预测控制（NMPC）等模型预测控制方法作为路径跟踪控制方法等。考虑到NMPC既能减少系统约束的影响,又无需人为设置预瞄距离,且对定位误差等扰动因素具有较强的鲁棒性,加之低速路径跟踪控制对实时性的需求较低,因此可以认为NMPC能够满足低速路径跟踪控制的绝大多数需求。高速路径跟踪控制在受系统约束影响之外,还面临着较高车速带来的行驶稳定性不足问题的挑战,因此常采用能够将动力学层面的复杂系统约束纳入考虑且计算成本较低的LMPC作为路径跟踪控制方法。不过仅采用动力学层面的LMPC控制方法无法完全解决高速路径跟踪控制中路径跟踪精确性和车辆行驶稳定性之间存在耦合的问题,目前常见的解决思路是在路径跟踪控制中加入额外的速度调节或权重分配模块。此外,在高速路径跟踪控制中,地面附着系数等环境参数的影响也较大,因此地面附着系数等环境参数的估算也成为了高速路径跟踪控制领域的重要研究方向。      

Scheduling problem for hot-rolling seamless steel tube production

Taking the seamless tube plant of Baoshan Iron & Steel Complex in China as the background,we analyze the characters of hot rolling seamless steel tube:multi varieties,low volume,complicated production process,flexible production routes.Then integrated scheduling problem for hot rolling seamless steel tube production is studied,which covers two key points;order-grouping problem and solution method for flowshop/jobshop scheduling problem.On the basis of these two problems,integrated scheduling decision system is developed.The design idea,function flow sheet,data processing method,and functional module of visualized human-computer interactive scheduling system implemented in seamless steel tube plant of Shanghai Baoshan Iron & Steel Complex are described into detail.Compared with manual system,the performance of system shows the applicability and superiority in several criteria.     

安装时间和机器受限的订单接受与并行机调度

订单接受与不相关并行机调度是订单接受与订单调度的联合决策, 广泛存在于面向定制的多品种混合生产环境中. 针对这一问题, 考虑了顺序与机器依赖的安装时间以及可加工机器限制, 并以最小化总成本为优化目标. 其中, 总成本由被接受订单的总拖期成本和被拒绝订单的总拒绝成本构成. 通过分析订单拒绝对目标的影响, 提出了列表拒绝方法和订单拒绝规则, 进而设计了协同进化遗传算法. 算法将染色体编码分解为订单列表和订单指派两个个体, 提出了基于列表拒绝方法的解码方案来进行订单拒绝决策. 由于两个个体相互独立, 且二者的进化约束不同, 因而引入协同进化策略, 并根据个体的编码特征, 分别采用单亲遗传算子和传统遗传算子进行遗传操作. 数据实验验证了算法的有效性和求解效率, 并对问题规模和订单拒绝成本对算法性能的影响进行了分析.      

Slip-Form Application to Concrete Structures

Because of superior speed and productivity, slip forms were extensively utilized as a potential formwork candidate in constructing concrete structures for the past few decades. Typical projects that employ this formwork technique are: Core of high-rise buildings, silos, telecommunication towers, cooling towers, heavy concrete offshore platforms, etc. The research presented in this paper aims at studying slip-form application to cores and silos, assessing its productivity, and determining its appropriate speed as well as auxiliary resource combinations. Simulation models are developed in which the potential control units in a slip-form system are described for cores and silos. Data are collected from several case study projects. A set of charts has been developed to predict productivity considering different stoppages, core cross section area, slipping (jacking) rate, and concrete placing methods. These charts play an essential role in managing slip-form application to cores and silos. Results show that the developed simulation models predict the productivity of case study projects with 99.70 and 99.30% accuracy for cores and silos, respectively. The presented research is relevant to both researchers and practitioners. It provides practitioners with charts that assist in scheduling and managing the required resources for slip-form application. In addition, it provides researchers with simulation models and framework for implementing slip forms to core and silo construction.     

Improving Satisfaction through Conflict Stimulation and Resolution in Value Management in Construction Projects

Value management is a goal-setting process that aims to satisfy the client’s project requirements. However, goals cannot always be easily identified or agreed upon due to conflicts among project participants and/or objectives. Conflict is often conceived of as detrimental to the effective operation of a team. Cognitive scientists argue that a suitable level of conflict can stimulate a team’s creativity, which could lead to better decision making, productivity, and satisfaction. This paper examines the relationships between the value-goal conflict and participants’ satisfaction through three case studies collected in Hong Kong. The findings indicate that a suitable level of conflict can improve satisfaction up to a certain point, where the satisfaction diminishes as conflict increases. To yield an optimum level of satisfaction, a value manager should stimulate conflicts at the early stage of the value management workshop and strive to resolve any undue conflicts among the project participants.     

Allocation of surgical procedures to operating rooms

Reduction of health care costs is of paramount importance in our time. This paper is a part of the research which proposes an expert hospital decision support system for resource scheduling. The proposed system combines mathematical programming, knowledge base, and database technologies, and what is more, its friendly interface is suitable for any novice user. Operating rooms in hospitals represent big investments and must be utilized efficiently. In this paper, first a mathematical model similar to job shop scheduling models is developed. The model loads surgical cases to operating rooms by maximizing room utilization and minimizing overtime in a multiple operating room setting. Then a prototype expert system which replaces the expertise of the operations research analyst for the model, drives the modelbase, database, and manages the user dialog is developed. Finally, an overview of the sequencing procedures for operations within an operating room is also presented.     

Computerized DSS for Construction Conflict Resolution under Uncertainty

Due to the inherent nature of construction projects, conflicts are unavoidable among the various parties involved. Such conflicts often delay projects and cause losses for all parties. This paper presents the development of a decision support system (DSS) to help in resolving construction disputes. The DSS integrates the elimination method to shortlist promising resolutions to a conflict, the graph model for conflict resolution to determine the best resolution that satisfies all decision makers’ preferences, and the information gap theory to consider uncertain decision preferences. A prototype system has been developed and a case study of a construction conflict used to demonstrate its features. The presented methodology for construction conflict resolution is useful for both researchers and practitioners to better deal with the dispute-prone nature of the construction industry under uncertainty and lack of information. In this paper, the proposed prototype successfully simulated and predicted the sequence of decisions that took place in the case study dispute, in the presence of uncertainty.     

Reconciliation of Owner and Contractor Views in Heavy Construction Projects

Delay and loss of productivity are the two main types of damage experienced by the contractor when the owner issues a change order. Courts have recognized critical path method schedule analysis as the preferred method of identifying and quantifying critical delays. As for the inefficiency damages, there is no direct way of measuring inefficiency due to its qualitative nature and the difficulty of linking the cause of the productivity loss to the damage. Most of the scholarly work published in this area was based on data supplied by the contractors; and that explains why there are discrepancies between what the contractor asks for and what the owner believes the contractor is entitled to. This study addresses the need for a statistical model to quantify the productivity loss from verifiable site data such as owner’s daily reports, change orders, drawings, and specifications, rather than rely solely on contractor surveys. A model is developed and validated to quantify the productivity loss in pipe work in roadway projects due to the change orders. The productivity loss study analyzed two sets of data that include: (1) variables that predict which of the two parties, the owner and the contractor, contributed to the productivity loss; and (2) variables that predict, from the legal viewpoint, productivity losses which only the owner is responsible for. The study showed the difference between what the contractor asked for and what he/she is actually entitled to. This model can be used by both the owner and the contractor to quantify the productivity loss due to change orders, and to offer an objective approach to reconcile their differences. This study concludes with an example to demonstrate the use of the model.     

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.