Comparison of Using Mixed-Integer Programming and Genetic Algorithms for Construction Site Facility Layout Planning

The use of modular construction has gained wide acceptance in the industry. For a specific construction facility layout problem such as site precast standardized modular units, it requires the establishment of an on-site precast yard. Arranging the precast facilities within a construction site presents real challenge to site management. This complex task is further augmented with the involvement of several resources and different transport costs. A genetic algorithm (GA) model was developed for the search of a near-optimal layout solution. Another approach using mixed-integer programming (MIP) has been developed to generate optimal facility layout. These two approaches are applied to solve with an example in this paper to demonstrate that the solution quality of MIP outperforms that of GA. Further, another scenario with additional location constraints can also be solved readily by MIP, which, however, if modeled by GA, the solution process would be complicated. The study has highlighted that MIP can perform better than GA in site facility layout problems in which the site facilities and locations can be represented by a set of integer variables.     

电炉CSP工艺开发无取向硅钢热带钢的技术可行性探讨

本文介绍了无取向硅钢产业的市场前景，并根据电炉CSP工艺状况，结合用户使用硅钢的成分和性能，提出了开发硅钢的初步工艺方案和看法。     

GA-QP Model to Optimize Sewer System Design

Sanitary sewer systems are fundamental and expensive facilities for controlling water pollution. Optimizing sewer design is a difficult task due to its associated hydraulic and mathematical complexities. Therefore, a genetic algorithm (GA) based approach has been developed. A set of diameters for all pipe segments in a sewer system is regarded as a chromosome for the proposed GA model. Hydraulic and topographical constraints are adopted in order to eliminate inappropriate chromosomes, thereby improving computational efficiency. To improve the solvability of the proposed model, the nonlinear cost optimization model is approximated and transformed into a quadratic programming (QP) model. The system cost, pipe slopes, and pipe buried depths of each generated chromosome are determined using the QP model. A sewer design problem cited in literature has been solved using the GA-QP model. The solution obtained from the GA model is comparable to that produced by the discrete differential dynamic programming approach. Finally, several near-optimum designs produced using the modeling to generate alternative approach are discussed and compared for improving the final design decision.     

Mathematical Model of Microstructure Evolution of X60 Line Pipe Steel During CSP Hot Rolling

An integrated process modelling system for simulating the microstructure evolution of Nb-microalloyed HSLA steel produced in CSP hot rolling process has been developed on the basis of the microstructure simulation and mechanical properties prediction technology. 3-D thermomechanical coupled finite element models for simulating hot strip rolling have been developed and the distribution of equivalent plastic strain through the thickness direction of the rolled material by CSP roiling was obtained. Thus the distribution of temperature, strain and strain rate through the thickness of the steel stocks, as well as the microstructure evolution during hot rolling of X60 line pipe steel strip has been investigated by using the developed integrated process modelling system. In addition, the determination and op-timization of controllable process parameters during CSP hot strip rolling for the Nb-microalloyed X60 line pipe steel have been implemented, and control strategies such as adopting larger pass reduction in the first stand, arranging ap-propriate pass interval times and proper rolling speed, to reduce or eliminate mixed grain microstructure of Nb micro-alloyed strip in CSP processing have been proposed.     

Mathematical Modelling on the Microstructure Evolution of X60 Line Pipe Steel during CSP Hot Rolling

 An integrated process modelling system for simulating the microstructure evolution of Nb-microalloyed HSLA steel produced in CSP hot rolling process has been developed on the basis of the microstructure simulation and mechanical properties prediction technology. Thermo-mechanical coupled finite element models for simulating hot strip rolling have been developed and the distribution of equivalent plastic strain through the thickness direction in the rolled material of CSP rolling was carried out. Thus the distribution of temperature, strain and strain rate through the thickness of the steel stocks, as well as the microstructure evolution during hot rolling of X60 line pipe steel strip have been investigated by using the developed integrated process modelling system. In addition the determination and optimization of controllable process parameters during CSP hot strip rolling for the Nb-microalloyed X60 line pipe steel have been implemented, and control strategies such as adopting larger pass reduction in the first stand, and arranging appropriate pass interval times and proper rolling speed, to reduce or eliminate mixed-grains microstructure of Nb microalloyed strip in CSP processing have been proposed.     

Hybrid Time-Cost Optimization of Nonserial Repetitive Construction Projects

Time-cost trade-off analysis represents a challenging task because the activity duration and cost have uncertainty associated with them, which should be considered when performing schedule optimization. This study proposes a hybrid technique that combines genetic algorithms (GAs) with dynamic programming to solve construction projects time-cost trade-off problems under uncertainty. The technique is formulated to apply to project schedules with repetitive nonserial subprojects that are common in the construction industry such as multiunit housing projects and retail network development projects. A generalized mathematical model is derived to account for factors affecting cost and duration relationships at both the activity and project levels. First, a genetic algorithm is utilized to find optimum and near optimum solutions from the complicated hyperplane formed by the coding system. Then, a dynamic programming procedure is utilized to search the vicinity of each of the near optima found by the GA, and converges on the global optima. The entire optimization process is conducted using a custom developed computer code. The validation and implementation of the proposed techniques is done over three axes. Mathematical correctness is validated through function optimization of test functions with known optima. Applicability to scheduling problems is validated through optimization of a 14 activity miniproject found in the literature for results comparison. Finally implementation to a case study is done over a gas station development program to produce optimum schedules and corresponding trade-off curves. Results show that genetic algorithms can be integrated with dynamic programming techniques to provide an effective means of solving for optimal project schedules in an enhanced realistic approach.     

Fuzzy Optimization Model for Earthwork Allocations with Imprecise Parameters

Existing linear programming (LP) models of earthwork allocations in roadway construction assume that unit cost coefficients of earthwork activities and borrow pits/disposal sites capacities are certain and deterministic numbers. However in real-world problems there are naturally some uncertainties inherited in these values, which make it difficult to represent a single value as the candidate of entire possible values. This paper presents a fuzzy linear programming (FLP) model of earthwork allocations based on the fact of assuming unit cost coefficients and borrow pits/disposal sites capacities as fuzzy numbers while minimizing total earth-moving cost as an objective function. A method based on α cuts of a fuzzy set is used to take the uncertainty in borrow pits/disposal sites capacities into account. The uncertainty in fuzzy cost coefficients of the objective function and its effects on decision variables of the earthwork allocations model are also considered using the method presented by Chanas and Kuchta in 1994. Subsequently, a more general model is suggested which considers both uncertainties in borrow pits/disposal sites capacities and cost coefficients simultaneously. It is demonstrated that the presented FLP, compared to a deterministic LP, introduces a more robust solution; as the result of giving fuzziness to the uncertain parameters. Such a solution could be beneficial in real world decision making where uncertainties on resources and activities cost exist.     

基于因素分析的炼钢车间布置评价模型

炼钢车间的布置直接可以影响到车间内的物流运行、生产调度、生产效率和生产成本。分析炼钢车间布置的发展特点,综合炼钢车间内的物流运输、天车运行、车间占地面积、建设成本等4个因素建立炼钢车间布置的评价模型,提出模型的求解思路,并应用模型对两种不同的炼钢车间布置进行分析和评价,比较两种布置的优劣,对于新/改建炼钢车间的整体布置具有一定的指导意义。     

包钢薄板坯连铸连轧Ι流段加热炉砌筑技术

文章阐述了包钢薄板坯连铸连轧加热车间加热炉砌筑的材料特点、结构特点及施工方法;同时对特殊部位及过程采取的技术措施进行了细致介绍.     

彩涂板生产线的节能与减排

介绍了彩涂板生产线的能源消耗量及目前的废气治理现状。阐述了彩涂板生产线排放物对环境的危害,提出了节能和废气治理的途径和方向。     

Multiobjective Transportation Planning for Waste Hauling

In the transportation planning for some industrial wastes, in addition to hauling cost, environmental impact must frequently be considered. A notable example is transporting waste soil generated by major construction projects. Adequate transportation planning is particularly important for construction in a metropolitan area. In this study, we present a novel two-phase approach to address the multiple-criteria decision problem. The first phase applies the fuzzy analytic hierarchy process to obtain a “composite impedance” for each road sector where transportation costs, environmental impact, and traffic congestion are considered in the evaluation. The second phase employs fuzzy mathematical programming to find the optimal transportation network based on the fuzzy impedance. An illustrative example is provided for the transportation planning for waste soil of the Kaohsiung mass rapid transit system construction project. The optimal solutions using the proposed approach are compared with the solutions using the conventional shortest-path approach where minimizing the transportation cost is the only objective.     

Conjoining MMAS to GA to Solve Construction Site Layout Planning Problem

An optimal construction site layout planning (CSLP) is vital for project management. It can reduce the transportation flows and thus the costs of a project. Genetic algorithm (GA) is the most used algorithm to solve site layout problems, but randomly generated initial population in GA will decrease solution quality. Max-min ant system (MMAS) can offer a better initial population than the randomly generated initial population at the beginning of GA. In this study, a modified GA (MMAS-GA) formed by conjoining MMAS to the step of initialization of GA is proposed to solve CSLP problems. In order to reveal the computational capability of MMAS-GA to solve CSLP problems, the results of MMAS-GA and traditional GA are compared by solving an equal-area CSLP problem. The results showed that the proposed MMAS-GA algorithm provided a better optimal solution under the objective function of minimizing the transportation flows between the site facilities. The proposed MMAS-GA algorithm could assist project managers and planners to design optimal construction site layout, and thus to reduce construction costs.     

Two-Stage Mathematical Programming Approach for Steelmaking Process Scheduling Under Variable Electricity Price

 The steelmaking process scheduling problem by considering variable electricity price (SMSPVEP) was investigated. A decomposition approach was proposed for the SMSPVEP. At the first stage, mathematical programming was utilized to minimize the maximum completion time for each cast without considering variable electricity price. At the second stage, based on obtained relative schedules of all casts, a mathematical model was formulated with an objective of minimizing the energy cost for all casts scheduling problem. The two-stage models were tested on randomly generated instances based on the practical process in a Chinese steelmaking plant. Computational results demonstrate the effectiveness of the proposed approach.     

Production Scheduling for Precast Plants using a Flow Shop Sequencing Model

There are two alternatives for production organization in precast factories—namely, the comprehensive method and the specialized method. Production scheduling under the specialized alternative has been found to be a difficult optimization problem if heterogeneous elements are involved. A flow shop sequencing model that incorporates actual constraints encountered in practice is proposed for this difficult case of precast production scheduling. The model is solved using a genetic algorithm (GA). The traditional minimize makespan and the more practical minimize tardiness penalty objective functions are optimized separately, as well as simultaneously using a normalized weighted GA. Comparisons between the GA and classical heuristic rules show that the GA can obtain good schedules for the model, giving a family of solutions that are at least as good as those produced by the use of heuristic rules.     

宝钢炼铁固体废物资源控制与综合利用

对宝钢炼铁系统固体废物资源控制与综合利用进行了总结分析。炼铁过程产生的大量固体废物资源是国内外钢铁企业所面临的共同难题,伴随着市场竞争的不断加剧和“循环经济”政策的引导,实现对固体废物资源的控制和综合利用越来越受到钢铁企业重视,近些年来,宝钢炼铁厂通过优化生产技术、开发新的回收技术和应用机会成本法实现了对固体废物资源的控制和综合利用,结果不仅未造成产品质量的下降,而且也成功实现了可观的经济效益。     

Decision Support System for Scheduling Steel Fabrication Projects

One of the most important and difficult problems faced by the steel fabrication industry is the planning and scheduling of shop activities. Competitive pressures force fabricators to disrupt schedules in progress to accommodate frequent requests from key customers for changes in design and/or delivery schedules. Capacity management is a complex problem and is key to proper management of manufacturing/fabrication activities. This paper presents a decision support system for planning and scheduling of steel fabrication projects. Although the immediate application of this approach is steel fabrication, its fundamental heuristic approach can be applied to any construction job shop scheduling exercise. Its main advantage over techniques such as CPM is that it is resource driven; its advantages over simulation techniques are its simplicity and overall schedule development time.     

Budget Allocation for Steel Bridge Paint Maintenance

Government authorities are responsible for managing their available budget so that they gain maximum benefit. Therefore, they must make intelligent decisions as to which projects will be funded and the degree of funding. Dynamic programming (DP), integer programming (IP), and greedy heuristic (GH) approaches have been applied to optimize a two-year budget allocation for repainting steel bridges in Indiana. The optimal solution and the objective function values resulting from application of DP, IP, and GH are similar. The Indiana Department of Transportation (INDOT) divides Indiana into six districts. The results show that District 1 has the highest budget allocation percentage (28%). It has the lowest percent in the first year and the highest percent in the second year. District 2 has the lowest percentage (11%). A sensitivity analysis has been completed to show the potential alternative solutions that assist INDOT decision makers in solving their budget allocation problems.     

Fuzzy Inexact Mixed-Integer Semiinfinite Programming for Municipal Solid Waste Management Planning

Based on the concept of functional intervals, fuzzy inexact mixed-integer semiinfinite programming (FIMISIP) method is developed for municipal solid waste management planning. The method allows the uncertainties in parameters expressed as fuzzy, interval, and functional interval numbers to be directly communicated into the programming problem. The FIMISIP problem is solved by dividing it into two interactive semiinfinite programming (SIP) subproblems. Solutions reflecting the inherent uncertainties can then be generated by combining the SIP solutions into a set of decision intervals. The method is applied to a municipal solid waste management planning system for demonstrating its effectiveness in dealing with uncertain and dynamic complexities. Compared to the previous inexact programming methods, FIMISIP has the advantages as follows: (1) the dynamic complexity can be addressed by introducing the functional-interval parameters associated with time into the programming problem; (2) the FIMISIP solutions provide a set of flexible waste-management schemes to the decision makers; and (3) the FIMISIP solutions are more reliable than those from the previous ILP ones since they can be “really” optimal regardless of how the parameters vary with time within the time period. While this study is a first attempt to solve solid waste management issues under complex uncertainties, the method can be extended to other environmental management planning problems.     

CSP热连轧机无取向硅钢边降控制技术研究与应用

 通过掌握CSP热连轧工艺生产无取向硅钢的工艺特点,分析了热轧无取向硅钢边降形成的机制,指出了热轧控制无取向硅钢边降的必要性。最后基于大量的现场跟踪测试及试验数据,提出了一套CSP热连轧工艺生产无取向硅钢的边降控制技术方案,并应用于工业现场,取得了明显效果,满足了下道冷轧工序的边降控制需求。     

热轧U型钢板桩切深孔型宽展模型的研究

利用铅试样在1:10相似比,轧辊直径130 mm,辊身长度265mm,最大轧制压力150 kN,电机功率5.5kW的实验轧机上对轧辊直径1200mm,辊身长度2200 mm,最大轧制力25000 kN,轧机功率1 000 kW的钢厂轧机进行孔型轧制模拟试验,研究0.1~0.5 mm压下量,轧辊直径97.72~107.65 mm,以及轧制润滑系数0.21~0.45对轧件宽度变化的影响。结果表明,轧制的型钢宽展随压下量增大,摩擦系数的增大而增加;将复杂非对称面进分部研究后合并影响的模式研究复杂断面型钢的宽展是可行的;获得的切深孔型宽展计算模型经实验室轧制变形测量证明是有效的。