Choquet optimal set in biobjective combinatorial optimization

We study in this paper the generation of the Choquet optimal solutions of biobjective combinatorial optimization problems. Choquet optimal solutions are solutions that optimize a Choquet integral. The Choquet integral is used as an aggregation function, presenting different parameters, and allowing to take into account the interactions between the objectives. We develop a new property that characterizes the Choquet optimal solutions. From this property, a general method to easily generate these solutions in the case of two objectives is defined. We apply the method to two classical biobjective optimization combinatorial optimization problems: the biobjective knapsack problem and the biobjective minimum spanning tree problem. We show that Choquet optimal solutions that are not weighted sum optimal solutions represent only a small proportion of the Choquet optimal solutions and are located in a specific area of the objective space, but are much harder to compute than weighted sum optimal solutions.     

基于遗传算法的双目标车辆路线优化研究

本文对车辆路线优化问题建立了双目标多旅行商问题模型，提出一种求解旅行商问题混合遗传算法，并对双目标多旅行商问题提出了解决方案。基于实例的仿真结果表明，文章提出的算法和解决方案是可行而有效的。     

Stochastic facility and transfer point covering problem with a soft capacity constraint

Existing models for transfer point location problems (TPLPs) do not guarantee the desired service time to customers. In this paper, a facility and TPLP is formulated based on a given service time that is targeted by a decision maker. Similar to real‐world situations, transportation times and costs are assumed to be random. In general, facilities are capacitated. However, in emergency services, they are not allowed to reject the customers for out of capacity reasons. Therefore, a soft capacity constraint for the facilities and a second objective to minimize the overtime in the facility with highest assigned demand are proposed. To solve the biobjective model with random variables, a variance minimization technique and chance‐constraint programming are applied. Thereafter, using fuzzy multiple objective linear programming, the proposed biobjective model is converted to a single objective. Computational results on 30 randomly designed experimental problems confirm satisfactory performance of the proposed model in reducing the variance of solutions as well as the overtime in the busiest facility.     

Three new metrics to measure the convergence of metaheuristics towards the Pareto frontier and the aesthetic of a set of solutions in biobjective optimization

In this paper, some new quality metrics concerning the evaluation of performances of biobjective optimization methods relating to the generation of the Pareto frontier are presented. A new metric for the calculation of the running speed of a multiobjective optimization method is also presented.These metrics are tested on two biobjective scalarization functions (Weighted sum and Tchebychev aggregation of objective functions) handled by a metaheuristic (Simulated Annealing).     

New reduction strategy in the biobjective knapsack problem

In this paper, the admissible region of a biobjective knapsack problem is our main interest. Although the reduction of feasible region has been studied by some authors, yet more investigation has to be done in order to deeply explore the domain before solving the problem. We propose, however, a new technique based on extreme supported efficient solutions combined with the dominance relationship between items' efficiency. An illustration of the algorithm by a didactic example is given and some experiments are presented, showing the efficiency of the procedure compared to the previous techniques found in the literature.     

Representation of the non-dominated set in biobjective discrete optimization

This paper introduces several algorithms for finding a representative subset of the non-dominated point set of a biobjective discrete optimization problem with respect to uniformity, coverage and the ϵ-indicator. We consider the representation problem itself as multiobjective, trying to find a good compromise between these quality measures. These representation problems are formulated as particular facility location problems with a special location structure, which allows for polynomial-time algorithms in the biobjective case based on the principles of dynamic programming and threshold approaches. In addition, we show that several multiobjective variants of these representation problems are also solvable in polynomial time. Computational results obtained by these approaches on a wide range of randomly generated point sets are presented and discussed.     

A real-time warehouse operations planning system for small batch replenishment problems in production environment

A factory consists of numerous production workstations, multiple production lines and many production floors. Due to the characteristics of just-in-time and make-to-order mode manufacturing, small batches of production materials are required for production lines within a short period of time in order to facilitate daily production operations. In this paper, a real-time warehouse operation planning system (R-WOPS) for solving small batch replenishment problems is described. Through using R-WOPS, real-time production and warehouse operations are monitored by radio frequency identification (RFID) technology, and a genetic algorithm (GA) technique is applied to formulate feasible small batch replenishment solutions. Simulation tests show that R-WOPS generates pick-up and delivery route plans for small batch replenishment orders very efficiently.     

A Dijkstra-like method computing all extreme supported non-dominated solutions of the biobjective shortest path problem

We address the problem of determining all extreme supported solutions of the biobjective shortest path problem. A novel Dijkstra-like method generalizing Dijkstra׳s algorithm to this biobjective case is proposed. The algorithm runs in O(N(m+n log n)) time to solve one-to-one and one-to-all biobjective shortest path problems determining all extreme supported non-dominated points in the outcome space and one supported efficient path associated with each one of them. Here n is the number of nodes, m is the number of arcs and N is the number of extreme supported points in outcome space for the one-to-all biobjective shortest path problem. The memory space required by the algorithm is O(n+m) for the one-to-one problem and O(N+m) for the one-to-all problem. A computational experiment comparing the performance of the proposed methods and state-of-the-art methods is included.     

Virtual factory as a useful tool for improving production processes

Virtual production in the virtual factory is a modern approach to support the production process and offers a possibility to achieve continuous progress at the logistical level of the organization of the production process.The first part of the paper presents an innovative approach of a virtual factory for use in SMEs with one off production. In the following, a virtual factory created on this basis and on real example of a tool shop is explained. With simple settings, the simulation of the defined production plans can be carried out quickly and the simulation results can be used to identify potential bottlenecks and thus to create an optimal production plan. In the third part, the built-in indicators are explained, which clearly characterized the state of the production process in the virtual factory. It is possible to identify the progress of each operation on a time axis. It is also possible to identify the expected utilization of production capacities depending on the various set of production parameters and the utilization of production processes by production capacity. And as the next option it is easy to determine the free production capacities for the selected period.     

基于GE PA的卷烟厂制丝线MES的设计

分析了卷烟厂制造执行系统的特点以及发展现状。以PA平台为基础,设计了一套卷烟厂制丝线的制造执行系统,主要由系统管理、生产建模、生产管理、质量管理、设备管理、人员管理等模块组成。该系统的开发大大提高了卷烟厂制丝车间的生产管理水平。     

Speed-up techniques for solving large-scale biobjective TSP

In this paper, we present the Two-Phase Pareto Local Search (2PPLS) method with speed-up techniques for the heuristic resolution of the biobjective traveling salesman problem. The 2PPLS method is a state-of-the-art method for this problem. However, because of its running time that strongly grows with the instances size, the method can be hardly applied to instances with more than 200 cities. We thus adapt some speed-up techniques used in single-objective optimization to the biobjective case. The proposed method is able to solve instances with up to 1000 cities in a reasonable time with no, or very small, reduction of the quality of the generated approximations.     

Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

Growth, crisis and future of the factory

The process of industrialization in the 19th century was coupled with the existence of the factory. The organization of the work within factories through the combination of manual and mechanical activities led to a substantial productivity increase and a significant improvement in living standards. The satisfaction of basic needs and consumer demands led initially to the refinement of products and production processes; while at a later stage they contributed to the crisis of the factory. Presumably a new period of growth for the factory starts due to the thrust of innovation in the information technology. The key element of the future production renewal is the computer integrated and flexible automated factory of the future, which provides a continuous production flow and ties together energy, materials and information. Substantial parts of the computer integrated production are communication networks, intelligent generation systems, computer-aided design (CAD), computer-aided planning (CAP), computer-aided manufacturing (CAM), computer-aided quality control (CAQ) and stimulation systems. These combine intelligent machine-tools, intelligent robots, intelligent assembly machines, intelligent inspection machines and intelligent means of transportation within the factory of the future. The artificial intelligence and the possibility of remote control due to the developments in the information technology are the prerequisites for the setting-up of new production schemes. Next to the central organized factories, new decentralized production structures can be developed which would make possible drastic changes in the social life.     

Intelligent scheduling approaches for a wafer fabrication factory

The production system of a wafer fabrication factory is a very complicated process. Job scheduling in a wafer fabrication factory is a very difficult task. To solve this problem, two intelligent scheduling rules are proposed in this study. The intelligent scheduling rules are modified from the well-known fluctuation smoothing rules with some innovative treatments. To evaluate the effectiveness of the proposed methodology, production simulation was also applied in this study. According to experimental results, the proposed methodology outperformed some existing approaches by reducing the average cycle time and cycle time standard deviation, the most important objectives of job scheduling in a wafer fabrication factory.     

汽车装配车间生产计划调度系统的设计与开发

论述了汽车装配车间在企业顺利生产中的重要性,建立了车间生产计划与调度的同时优化模型。基于免疫算法以概率1收敛的特点,选用免疫算法并将之进行适当组合得到交替式免疫算法来对该模型进行求解,以达到计划和调度同时优化的目的。在进行理论研究的基础上,根据南京某汽车厂的实际需求设计出了生产计划与调度系统方案,并使用组件化技术,开发出了基于．NET平台和B／S模式的汽车装配车间生产计划与调度系统,最终满足实际生产要求,达到了高效信息管理的目标。     

Software factory principles, architecture, and experiments

The software factory concept which symbolizes a desired paradigm shift from labor-intensive software production to a more capital-intensive style in which substantial investments can be made at an acceptable risk level is discussed. Most traditional software environments emphasize support for producing code and associated documents. In a software factory, the focus shifts to coordinating information between producers and consumers so that the right person always has the right information at the right time. A CASE environment architecture and two factory experiments, one a prototype software factory environment for real-time system development, and the other a factory for exploring information logistics, are reviewed     

The biobjective integer minimum cost flow problem—incorrectness of Sedeño-Noda and Gonzàlez-Martin's algorithm

In this paper, we show with a counterexample, that the method proposed by Sedeño-Noda and Gonzàlez-Martin for the biobjective integer minimum flow problem is not able to find all efficient integer points in objective space.     

数字化工厂技术在生产线规划中的应用

以分析数字化工厂技术的应用效果为目的,讨论虚拟环境中的生产线规划,介绍数字化工厂软件eM-Power,并举例说明在其生产线仿真优化工具eM-Plant环境下进行生产线建模仿真、分析瓶颈设备的过程,证明数字化工厂技术在制造业领域的良好应用前景.     

Stochastic models and numerical solutions for manufacturing/remanufacturing systems with applications to the printer cartridge industry

This paper investigates the production rates control of a hybrid manufacturing/remanufacturing system in a closed-loop environment, with application to the printer cartridge industrial sector. The system studied comprises manufacturing and remanufacturing factories working in parallel, and subject to random failures and repairs. The failure rate of the manufacturing factory depends on its production rate, while the failure rate is constant for the remanufacturing factory. Given the dependence of the failure rate on the production rate of the manufacturing factory, a non-homogeneous Markov process is used to describe the dynamics of the overall production system. The objective of the control problem concerns the minimization of a cost function which penalizes the presence of waiting customers, the inventory of finished parts, and the inventory of parts returned from customers upon reaching the end of their lives. Using a real business case study adapted from a leading European company producing printer cartridges, we obtain the optimal production policies for the both factories. Sensitivity analyses are conducted to illustrate the usefulness of the proposed approach and its applicability to other cases.     

Computing all efficient solutions of the biobjective minimum spanning tree problem

A common way of computing all efficient (Pareto optimal) solutions for a biobjective combinatorial optimisation problem is to compute first the extreme efficient solutions and then the remaining, non-extreme solutions. The second phase, the computation of non-extreme solutions, can be based on a “k-best” algorithm for the single-objective version of the problem or on the branch-and-bound method. A k-best algorithm computes the k-best solutions in order of their objective values. We compare the performance of these two approaches applied to the biobjective minimum spanning tree problem. Our extensive computational experiments indicate the overwhelming superiority of the k-best approach. We propose heuristic enhancements to this approach which further improve its performance.