AN EFFICIENT META-HEURISTIC ALGORITHM FOR ROUTING PRODUCT COLLECTING VEHICLES OF DEHYDRATION PLANTS. I. ALGORITHM DEVELOPMENT

Dehydration plants are characterized by a multi-product nature chiefly attributed to the utilization of different raw materials to be processed in parallel so that demand constraints are met. The Just-In-Time production planning policy of these plants require the collection of raw materials to be dehydrated shortly before the actual processing, immediately after harvesting. One of the most important aspects in collection of plant fresh products, is routing of collecting vehicles, so that total collection time is minimized. The aim of this study is to describe a new stochastic search meta-heuristic algorithm for solving the Vehicle Routing Problem (VRP), termed as the Backtracking Adaptive Threshold Accepting (BATA) algorithm. Our effort focuses on developing an innovative method, which produces reliable and high quality solutions, requiring reasonable computing effort. The main innovation of the algorithm, toward a typical threshold accepting algorithm, is that during the optimization process the value of the threshold is not only lowered, but also raised or backtracked according to how effective a local search is. This adaptation of the value of the threshold, plays an important role in finding high quality routing solutions. BATA is described in detail while its performance and characteristic case studies are presented by Tarantilis and Kiranoudis (2000).     

A THRESHOLD-ACCEPTING METAHEURISTIC METHOD FOR SCHEDULING THE OPERATIONS OF DEHYDRATION PLANTS

Dehydration plants are broadly characterized by a multi-product nature chiefly attributed to the utilization of different raw materials to be processed sequentially so that demand constraints are met. Processing of raw materials is implemented through a series of preprocessing operations that together with drying constitute the production procedure of a pre-specified programme. The core of the manufacturing system that a typical dehydration plant involves, is scheduling of operations so that demand is fulfilled within a pre-determined time horizon imposed by production planning. The typical scheduling operation that dehydration plants involve can be formulated as a general job shop scheduling problem. The aim of this study is to describe a new metaheuristic method for solving the job shop scheduling problem of dehydration plants, termed as the Backtracking Adaptive Threshold Accepting (BATA) method. Our effort focuses on developing an innovative method, which produces reliable and high quality solutions, requiring reasonable computing effort. The main innovation of this method, towards a typical threshold accepting algorithm, is that during the optimization process the value of the threshold is not only lowered, but also raised or backtracked according to how effective a local search is. BATA is described in detail while a characteristic job shop scheduling case study for dehydration plant operations is presented.     

A THRESHOLD-ACCEPTING METAHEURISTIC METHOD FOR SCHEDULING THE OPERATIONS OF DEHYDRATION PLANTS

ABSTRACT

Dehydration plants are broadly characterized by a multi-product nature chiefly attributed to the utilization of different raw materials to be processed sequentially so that demand constraints are met. Processing of raw materials is implemented through a series of preprocessing operations that together with drying constitute the production procedure of a pre-specified programme. The core of the manufacturing system that a typical dehydration plant involves, is scheduling of operations so that demand is fulfilled within a pre-determined time horizon imposed by production planning. The typical scheduling operation that dehydration plants involve can be formulated as a general job shop scheduling problem. The aim of this study is to describe a new metaheuristic method for solving the job shop scheduling problem of dehydration plants, termed as the Backtracking Adaptive Threshold Accepting (BATA) method. Our effort focuses on developing an innovative method, which produces reliable and high quality solutions, requiring reasonable computing effort. The main innovation of this method, towards a typical threshold accepting algorithm, is that during the optimization process the value of the threshold is not only lowered, but also raised or backtracked according to how effective a local search is. BATA is described in detail while a characteristic job shop scheduling case study for dehydration plant operations is presented.     

AN EFFICIENT META-HEURISTIC ALGORITHM FOR ROUTING PRODUCT COLLECTING VEHICLES OF DEHYDRATION PLANTS. II. ALGORITHM PERFORMANCE AND CASE STUDIES

Routing of vehicle fleet for collecting newly cropped raw materials for multi-product dehydration plants is a component of plant production schedule of utmost significance. A meta-heuristic algorithm for efficiently solving the collecting vehicle routing problem was developed and analyzed in detail in Tarantilis and Kiranoudis (2000). Meta-heuristic algorithms are broadly characterized by a stochastic nature in producing tender solution configurations in linear search terms, which sweep the huge solution space in a guided and rational way. Algorithm performance is examined through an analysis of the impact of model parameters on solution procedure during the execution of typical routing problems. The most important model parameter examined was found to be the value of the initial threshold as well as the way that the value of this actual parameter is appropriately adjusted during the optimization process. The main characteristic of the algorithm is the way that threshold is not only lowered but also raised, or backtracked, depending on the success of the inner loop iterations to provide for an acceptable new solution that would replace an older one. An important feature of the algorithm is the fact that appearance of better configurations within a process run is distributed according to the Poisson probability distribution. The suggested algorithm is tested against typical literature benchmarks as well against real-world problem encountered in the production planning procedures of dehydration plants in Greece.     

AN EFFICIENT META-HEURISTIC ALGORITHM FOR ROUTING PRODUCT COLLECTING VEHICLES OF DEHYDRATION PLANTS. II. ALGORITHM PERFORMANCE AND CASE STUDIES

Routing of vehicle fleet for collecting newly cropped raw materials for multi-product dehydration plants is a component of plant production schedule of utmost significance. A meta-heuristic algorithm for efficiently solving the collecting vehicle routing problem was developed and analyzed in detail in Tarantilis and Kiranoudis (2000). Meta-heuristic algorithms are broadly characterized by a stochastic nature in producing tender solution configurations in linear search terms, which sweep the huge solution space in a guided and rational way. Algorithm performance is examined through an analysis of the impact of model parameters on solution procedure during the execution of typical routing problems. The most important model parameter examined was found to be the value of the initial threshold as well as the way that the value of this actual parameter is appropriately adjusted during the optimization process. The main characteristic of the algorithm is the way that threshold is not only lowered but also raised, or backtracked, depending on the success of the inner loop iterations to provide for an acceptable new solution that would replace an older one. An important feature of the algorithm is the fact that appearance of better configurations within a process run is distributed according to the Poisson probability distribution. The suggested algorithm is tested against typical literature benchmarks as well against real-world problem encountered in the production planning procedures of dehydration plants in Greece.     

浅谈埃塞俄比亚水泥厂原燃料的特点

埃塞俄比亚地质形成期较短,且具高原国家构造活动复杂的特质,埃塞俄比亚的水泥厂所使用的原料、燃料、混合材料等具有其特定的资源禀赋特征.其中,砂岩的成熟度较高,对于生料粉磨和烧成均具有一定的影响;黏土中铁质含量高,一般不需要加入铁质校正原料;混合材主要为天然物料-浮石、火山灰、凝灰岩、石灰石等;当地的燃料以褐煤为主,其热力...     

A rule-based genetic algorithm for the scheduling of single-stage multi-product batch plants with parallel units

This paper presents a heuristic rule-based genetic algorithm (GA) for large-size single-stage multi-product scheduling problems (SMSP) in batch plants with parallel units. SMSP have been widely studied by the researchers. Most of them used mixed-integer linear programming (MILP) formulation to solve the problems. With the problem size increasing, the computational effort of MILP increases greatly. Therefore, it is very difficult for MILP to obtain acceptable solutions to large-size problems within reasonable time. To solve large-size problems, the preferred method in industry is the use of scheduling rules. However, due to the constraints in SMSP, the simple rule-based method may not guarantee the feasibility and quality of the solution. In this study, a random search based on heuristic rules was proposed first. Through exploring a set of random solutions, better feasible solutions can be achieved. To improve the quality of the random solutions, a genetic algorithm-based on heuristic rules has been proposed. The heuristic rules play a very important role in cutting down the solution space and reducing the search time. Through comparative study, the proposed method demonstrates promising performance in solving large-size SMSP.     

A genetic‐algorithm‐based optimal scheduling system for full‐filled tanks in the processing of starting materials for alumina production

Due to the instability of mine sources and the uncertainty of the composition of returned lye and waste liquid, there exists a significant fluctuation of raw slurry quality in the blending process of starting materials for sintering. The expected slurry was obtained through the mixing of starting materials in full‐filled tanks. In this article, an optimal scheduling model of full‐filled tanks is developed based on material balance principle and expert experiences subject to technological requirements. To solve such optimization problem, an improved genetic algorithm (IGA) is proposed, in which the intervention strategy is introduced into the random process of population initialization to obtain the well‐proportioned initial population and the probabilities of crossover and mutation are changed according to the difference between the fitness value of the best solution and the average fitness value of the better solutions as well as the difference between the fitness value of the best solution and the average fitness value of the current population to prevent premature convergence. The IGA‐based optimization system was applied to the processing of raw slurry for alumina production and the actual running results show that the composition fluctuation in mixed raw slurry decreased significantly, effectively improving the eligibility rate of the mixed raw slurry and contributing to the stabilization of the subsequent process of alumina production.     

全局优化搜索新算法──列队竞争算法(Ⅱ)解网络综合问题

本文给出了列队竞争算法解组合优化问题的框架和确定变异领域的两条原则 .对管路网络综合问题和换热网络综合问题确定了相应的变异领域 ,用列队竞争算法分别解这两个网络综合问题 ,所得到的最优解优于文献报道的结果 .     

Abwasser zu Prozesswasser – zwei unterschiedliche Ansätze

Wastewater reuse and recycling will play an increasingly important role in solving future water stress worldwide. Water of high quality and purity is an indispensable raw material for industry in many production steps, so the availability of water is a decisive location factor for industry. Innovative concepts for wastewater reuse and recycling within the framework of operator models based on many years of know-how lead to the conservation of scarce water resources and to a sustainable and financially attractive water supply. As the presented reference plants show, ecologically and economically advantageous solutions can be created for municipalities, industry, and water suppliers.     

陶瓷原料质量评价方法研究

陶瓷原料质量受诸多因素影响,合适的原料是生产优质陶瓷产品的保证。本文通过一系列的应用研究,探讨了陶瓷原料的质量评价方法,以保证选取适当的陶瓷原料,为生产出高质量的陶瓷产品奠定基础。     

基于多层次模糊综合评判的陶瓷原料质量评价

陶瓷原料质量受诸多因素的影响,合适的原料是生产优质陶瓷产品的保证。论述了如何运用模糊数学中的多层次决策模型来对陶瓷原料进行综合评判,以保证选取适当的陶瓷原料,为生产出高质量的陶瓷产品奠定基础。     

Thoughts on Strategic Development of China‘s Refractories Industry

For China‘s refractories industry, the first two decades in the new century would be a period of structural optinization with reorganization of refractories enterprises, reconstruction of manufacturing plants and restructuring of product varieties. An important strategic measure should be to develop high quality synthetic raw materials and high performance functional products mainly based on our rich natural resources to cope with new demands of advanced high temperature technologies.     

Zukunftssichere und umweltneutrale Beseitigung von Industrieabfällen

Low environmental-impact disposal of solid, liquid and semisolid industrial residues . In many production plants, waste residues are formed which must be treated before their disposal so as to safeguard against environmental pollution. Industrial methods for the treatment and disposal of residues are so multifarious that each disposal problem requires careful consideration so as to ensure selection of the most suitable method, both from the ecological and economical point of view. Dumping grounds cannot accommodate all waste materials without endangering or disturbing the environment. For incineration, proven methods are available which can be modified to suit the particular waste problem at hand. After a suitable pretreatment every effort must be made to achieve a waste free from organic materials, an optimum utilization of heat and a flue gas purification without inadmissible loading of waste gases and waters. In recent years there has been a considerable increase in research and development activities in the area of thermal treatment of solid, liquid and semi-solid wastes. Worth mentioning are the high-temperature methods giving favourable emission values and methods for degasification and gasification directed at the recovery of important raw materials. Plants based on these principles are currently being operated on the pilot scale.     

Controlling factors of the particle size of spherical silica synthesized by a dry process

Silica is an important inorganic compound used in many materials, including quartz products and resin fillers. To synthesize silica by a dry process, combustion methods using organosilicon compounds as raw monomers have been extensively studied. However, few studies have considered mass production or compared preparation methods using different types of organosilicon compounds and the same equipment. In this study, we used six starting materials in a dry process and examined the effect of monomer species on particle shape and size. The amount of raw monomer supplied was adjusted so that the calorific value of combustion was the same for all the raw monomers. We focused on the calorific value because it affects the construction cost of industrial-scale production plants. For example, when the calorific value is high, the manufacturing plant is large and costly because the heat generated after the reaction must be removed. We obtained spherical silica particles by a dry process using six monomers. The particle size depended on both the basic unit of the monomer and the required oxygen (RO) ratio of the primary burner gas. This combination was essential in determining the speed of the initial reaction, number of nuclei, and residence time. Consequently, we established a factor that determines the size of spherical silica particles and successfully adjusted the particle size.     

Method of raw materials selection for production of the MgO-C bricks of comparable properties using PCA and K-medoids

MgO-C refractories are zonally installed in most of the key heat devices of steel and iron metallurgy with the exposure to various corrosive factors. One of the most significant factors is low-temperature decarburization resulting in the oxidation of carbon in MgO-C refractories and loss of its properties. Moreover MgO-C materials are exposed for direct attack of liquid slag or steel melt which easily infiltrate the porous, decarburized hot face of the bricks. Cost of MgO-C materials of high quality is important for refractories user. For this reason researches try to develop materials of high quality but with lower cost by substituting fused raw materials with sintered ones or with recycled MgO-C. In this article, method of selecting the raw materials for production of MgO-C bricks with comparable properties is shown. Twenty different variants of MgO-C materials were prepared with the use of various quality raw materials. Basic properties of the industrially produced MgO-C bricks were measured. To select recipes with similar quality principal components analysis method and K-medoids algorithm were applied. To verify the results corrosion resistance of selected MgO-C materials were tested with the use of induction furnace of medium frequency.     

改进的AEA算法及其在重油热解模型参数估计中的仿真研究

着眼于AEA算法本身的不足点,通过更合理地给定其每一代的行走步长,提出一个改进的AEA算法(IAEA)来提高AEA算法的寻优性能。鉴于行走步长对于进化的不同阶段全局搜索和局部搜索之间的关系影响,今提出IAEA的步长应随着实际进化的不同阶段而合理地变化,以使得算法能跳出局部最优,避免早熟现象的发生。IAEA算法在7个典型测试函数上进行了测试,测试结果表明,与基本AEA算法、PSO和DE算法相比,IAEA的寻优性能有了很大的提高,不仅获得的解的质量更好,而且算法的稳定性都得到了提高。最后将IAEA算法用于重油热解模型参数估计的仿真研究中,通过验证,得到了更有利的结果,说明文中提出的算法是有效的。     

影响炭质中间相形成和发展的因素——Ⅰ.原料和热缩聚条件

炭质中间相是制备炭材料,尤其是高附加值炭材料的优质前驱体。它在高性能炭纤维、超高功率电极用针状焦、锂离子二次电池负极、超高比表面积活性炭及催化剂载体、泡沫炭等领域得到了较好的应用。综述了原料和热缩聚条件对炭质中间相形成和发展的影响,这些影响因素包括原料的种类、热缩聚温度、反应压力和保温时间等。通过讨论指出,由于炭质中间相涉及的原料种类多样,热缩聚制备过程中涉及的反应、物相复杂,因此,在制备特定性能的产品时,应针对产品的特定性能要求来选择原料、设定热缩聚条件,以制得具有最佳结构和性能的产品。     

水口山八厂制酸系统固氟降氯的改造总结

介绍了湖南水口山有色金属集团有限公司第八冶炼厂制酸系统氟氯状况及危害。针对企业实际,采取源头把控原料质量、降低冶炼烟尘率、优化净化工艺指标、投加水玻璃除氟、加大稀酸外排量等措施固氟降氯。技术改造后,稀酸含氟质量浓度低于行业经验值0.3 g/L,稀酸含氯质量浓度接近行业经验值0.3 g/L,冶炼装置作业率大幅度提升。     

AN ALGORITHM FOR SUPERVISORY MULTIVARIABLE CONSTRAINED OPTIMIZATION OF INDUSTRIAL PROCESSES

An algorithm is presented for supervisory optimization of industrial processes that integrates the minimization of operating costs with process operating constraints. It is assumed that the supervisory algorithm manipulates the set points of a lower-level control system and that the set points are updated at long enough intervals of time so that the process reaches steady state between set point updates. This steady state assumption greatly simplifies the algorithm computations and, more importantly, significantly reduces the effort required for process identification. This article develops the algorithm and then presents results from its application to a simulated distillation train. The simulation parallels an application of the algorithm to an actual industrial train on a commercial distributed control system.