Scheduling hybrid flowshops with sequence dependent setup times to minimize makespan and maximum tardiness

This article addresses the problem of scheduling hybrid flowshops where the setup times are sequence dependent to minimize makespan and maximum tardiness. To solve such an NP-hard problem, we introduce a novel simulated annealing (SA) with a new concept, called “Migration mechanism”, and a new operator, called “Giant leap”, to bolster the competitive performance of SA through striking a compromise between the lengths of neighborhood search structures. We hybridize the SA (HSA) with a simple local search to further equip our algorithm with a new strong tool to promote the quality of final solution of our proposed SA. We employ the Taguchi method as an optimization technique to extensively tune different parameters and operators of our algorithm. Taguchi orthogonal array analysis is specifically used to pick the best parameters for the optimum design process with the least number of experiments. We established a benchmark to draw an analogy between the performance of SA with other algorithms. Two basically different objective functions, minimization of makespan and maximum tardiness, are taken into consideration to evaluate the robustness and effectiveness of the proposed HSA. Furthermore, we explore the effects of the increase in the number of jobs on the performance of our algorithm to make sure it is effective in terms of both the acceptability of the solution quality and robustness. The excellence and strength of our HSA are concluded from all the results acquired in various circumstances.     

An ant colony algorithm for scheduling in flowshops with sequence-dependent setup times of jobs

The problem of scheduling in flowshops with sequence-dependent setup times of jobs is considered and solved by making use of ant colony optimization (ACO) algorithms. ACO is an algorithmic approach, inspired by the foraging behavior of real ants, that can be applied to the solution of combinatorial optimization problems. A new ant colony algorithm has been developed in this paper to solve the flowshop scheduling problem with the consideration of sequence-dependent setup times of jobs. The objective is to minimize the makespan. Artificial ants are used to construct solutions for flowshop scheduling problems, and the solutions are subsequently improved by a local search procedure. An existing ant colony algorithm and the proposed ant colony algorithm were compared with two existing heuristics. It was found after extensive computational investigation that the proposed ant colony algorithm gives promising and better results, as compared to those solutions given by the existing ant colony algorithm and the existing heuristics, for the flowshop scheduling problem under study.     

Cloud manufacturing service selection optimization and scheduling with transportation considerations: mixed-integer programming models

Cloud manufacturing is an emerging service-oriented manufacturing paradigm that integrates and manages distributed manufacturing resources through which complex manufacturing demands with a high degree of customization can be fulfilled. The process of service selection optimization and scheduling (SSOS) is an important issue for practical implementation of cloud manufacturing. In this paper, we propose new mixed-integer programming (MIP) models for solving the SSOS problem with basic composition structures (i.e., sequential, parallel, loop, and selective). Through incorporation of the proposed MIP models, the SSOS with a mixed composition structure can be tackled. As transportation is indispensable in cloud manufacturing environment, the models also optimize routing decisions within a given hybrid hub-and-spoke transportation network in which the central decision is to optimally determine whether a shipment between a pair of distributed manufacturing resources is routed directly or using hub facilities. Unlike the majority of previous research undertaken in cloud manufacturing, it is assumed that manufacturing resources are not continuously available for processing but the start time and end time of their occupancy interval are known in advance. The performance of the proposed models is evaluated through solving different scenarios in the SSOS. Moreover, in order to examine the robustness of the results, a series of sensitivity analysis are conducted on key parameters. The outcomes of this study demonstrate that the consideration of transportation and availability not only can change the results of the SSOS significantly, but also is necessary for obtaining more realistic solutions. The results also show that routing within a hybrid hub-and-spoke transportation network, compared with a pure hub-and-spoke network or a pure direct network, leads to more flexibility and has advantage of cost and time saving. The level of saving depends on the value of discount factor for decreasing transportation cost between hub facilities.     

Optimization techniques for machining operations: a retrospective research based on various mathematical models

Simulated annealing, genetic algorithm, and particle swarm optimization techniques have been used for exploring optimal machining parameters for single pass turning operation, multi-pass turning operation, and surface grinding operation. The behavior of optimization techniques are studied based on various mathematical models. The objective functions of the various mathematical models are distinctly different from each other. The most affecting machining parameters are considered as cutting speed, feed, and depth of cut. Physical constraints are speed, feed, depth of cut, power limitation, surface roughness, temperature, and cutting force.     

Effects of mathematical models and algorithms on quantitative characterization of areal step height with optical and stylus profilometers

Step height characterization is essential for the quality control of various functional components, such as graphene and the step features of semiconductor devices. Two methods are proposed to characterize the areal step heights. The first method extends the two-dimensional characterization in the ISO specification into a three-dimensional one by extracting multiple parallel profiles. The second method calculates the step heights by projecting from the measurement points to the normal vector at the surface centroid. Mathematical models and algorithms of the two methods are introduced and validated by synthetic data. Experiments are conducted by comparing the assessment results of the two methods and of a method proposed in a previous research. The calibrated values of the standards are utilized for validation. The characterization results may differ notably or slightly, depending on the properties of the data and the algorithm.     

Group scheduling with independent setup times, ready times, and deteriorating job processing times

Self-piercing riveting (SPR) is a high-speed mechanical fastening technique which is suitable for point-joining advanced lightweight sheet materials that are dissimilar, coated, and hard to weld. Major advances have been made in recent years in SPR technique. Latest literature relating to finite element analysis (FEA) of SPR joints is reviewed in this paper. The recent development in FEA of SPR joints are described with particular reference to three major factors that influence the success of SPR technique: SPR process, failure mechanism, and mechanical behavior of SPR joints. The main FE methods used in FEA of SPR joints are discussed and illustrated with brief case studies from the literature. Areas where further useful progress can be made are also identified.     

产品设计过程模型、策略与方法综述

根据工业化国家工程设计的发展,介绍了顺序过程、以设计为中心、并行设计和动态过程四种设计过程模型,产生多个还是一个概念的两种设计策略,及在不同设计阶段可选择的设计方法。对我国企业在开发新产品过程中选择设计过程模型、策略与方法有一定的参考意义。     

微机配料秤常见问题及解决方法

介绍微机配料秤在运行中经常出现的故障现象及故障的技术因素和对这些故障现象该怎样处理.     

称重显示仪表的不正常跳数及其处理方法

笔者针对称重显示仪表的几种跳数现象做出相应的处理方法，希望这些经验能够为广大用户提供有效的帮助。     

Single-machine group scheduling with linearly decreasing time-dependent setup times and job processing times

This paper considers single-machine scheduling problems with group technology (GT). We consider the case of group setup times and job processing times are a decreasing function of their starting time. We first prove that the makespan minimization problem remains polynomially solvable under the general decreasing linear deterioration. We then prove that the total weighted completion time minimization problem remains polynomially solvable under the proportional decreasing linear deterioration.     

虚拟企业伙伴选择模型与方法研究的进展

对近年来国内外虚拟企业伙伴选择模型与方法的研究进展作了综述。首先,对伙伴选择的研究进行了分类;然后,分别介绍了个体决策情况下的关于单任务与多任务的伙伴选择研究现状以及群决策情况下的伙伴选择研究现状;最后,对今后的主要研究工作进行了展望.     

Power system state estimation solution using modified models of PSO algorithm: Comparative study

The objective of all power system state estimation (PSSE) is to determine, by statistical projections, the best estimate of state variables represented by the voltage magnitudes and voltage angles of all the buses. Due to the complexity and non-linearity of the power system (PS), it is necessary to use more advanced methods for its analysis and control in real-time environment. This research discusses the application and the comparison of hybrid models of one of the algorithm using artificial intelligence (AI) technique (particle swarm optimisation ‘PSO’) in minimising the raw measurement errors in order to estimate the optimal point of the PS when certain sensitive data are incomplete. The effectiveness of the hybrid models are demonstrated and compared with the original PSO, artificial bee swarm optimisation (ABSO) algorithm and genetic algorithm (GA) using IEEE 14, 30, 118 and 300 bus test systems. Newton-Raphson load flow solution is taken as benchmark. Two different objective function formulations assessed by PSWV (Particle swarm without velocity equation), EPSOWP (Enhanced particle swarm optimiser incorporating a weighted particle), PSO-RF (PSO with repulsion factor) and CLPSO (Comprehensive learning PSO). The first formulation is the Weighted Least Square (WLS) and the second one is the Weighted Least Absolute Value (WLAV).     

CAPP的关键问题及其对策

首先评述了计算机辅助零件工艺过程设计的研究现状及趋势。之后 ,分析了 CAPP研究中的几个关键问题——工艺设计针对性强、专家系统技术的固有缺陷、工艺路线决策和工艺信息表达输入的困难。同时提出了解决这些问题的方法。     

Dynamic job-shop scheduling with sequence-dependent setup times: simulation modeling and analysis

This paper presents the salient aspects of a simulation-based experimental study of scheduling rules for scheduling a dynamic job shop in which the setup times are sequence-dependent. A discrete event simulation model of the job shop system is developed for the purpose of experimentation. Seven scheduling rules from the literature are incorporated in the simulation model. Five new setup-oriented scheduling rules are proposed and implemented. Simulation experiments were conducted under various experimental conditions characterized by factors such as shop load, setup time ratios, and due date tightness. The results indicate that setup-oriented rules provide better performance than ordinary rules. The difference in performance between these two groups of rules increases with the increase in shop load and setup time ratio. One of the proposed rules performs better for mean flow time and mean tardiness measures.     

Comparison of solution behaviour for three models of pressure-dependent plasticity: A simple analytical example

The main objective of the present paper is to compare, by means of a problem permitting a closed-form solution, qualitative behaviour of solutions based on three models of pressure-dependent plasticity, the coaxial model, the double-shearing model, and the double-slip and rotation model. The constitutive equations of each model reduce to classical metal plasticity at specific values of input parameters. Nevertheless, the solution behaviour essentially depends on the model chosen, independently of how close the input parameters are to these specific values. In particular, such features of the solutions as non-uniqueness, non-existence and singularity are emphasized. It is concluded that the double-slip and rotation model only retains all features inherent to classical plasticity.     

Scheduling with deteriorating jobs and past-sequence-dependent setup times

In this paper, we presented a scheduling model in which the deteriorating jobs and the setup times are considered at the same time. Under the proposed model, the actual job processing time is a general function of the processing times of jobs already processed and its scheduled position, while the setup time is past-sequence-dependent. We provided the optimal schedules for some single-machine scheduling problems.     

Parallel solution of creep and heat-conduction problems by means of nonlinear generalized models

A method of parallel solution of the steady creep and heat-conduction problems is proposed, on the basis of decomposition of the structure and approximate nonlinear models of the deformation of the structural components. An ANSYS program implements this method. Calculations confirm the effectiveness of the proposed algorithm.     

A comparison of methods to evaluate the behavior of finite element models with rough surfaces

Finite element (FE) modeling of rough surfaces is becoming increasingly common. However, the quality of the assumptions being made in these models, and thus the quality of the models themselves, is often unclear. Decisions about the geometry of the surface to be modeled, including the size of the surface to be modeled, the lateral resolution of the measured surface data to be used, and the formulation of the probabilistic surface to be used, can have a significant effect on a model's behavior. Similarly, varying model parameters, including the FE mesh density, can change the results by a factor of three or more. This work examines some of the metrics that can be used to evaluate the influence of these assumptions and parameters on FE models with rough surfaces and discusses the relative merits of each option. In particular, qualitative comparison of result plots, quantitative comparison and convergence of results parameters, qualitative and quantitative comparison of distributions of result values over various model dimensions, and more sophisticated comparison techniques inspired by image and signal processing are discussed.     

Iterated hybrid metaheuristic algorithms for unrelated parallel machines problem with unequal ready times and sequence-dependent setup times

The problem considered in this paper involves a set of independent jobs on unrelated parallel machines with sequence-dependent setup times and unequal ready times, and the objective is to minimize the weighted number of tardy jobs. Iterated hybrid metaheuristic algorithms are proposed to address this problem. The algorithms begin with effective initial solution generators to generate initial feasible solutions; then, hybrid metaheuristics are applied to improve the initial solutions, integrating the principles of the variable neighborhood descent approach and tabu search. If the search becomes trapped at a local optimum, a perturbation operator is developed to help the search escape. To evaluate the performance of the suggested algorithms, heuristic rules and iterated local search algorithms are examined and compared. Computational experimental results show that the proposed algorithms outperform the other heuristics.