A Differential Evolution-Based Algorithm to Schedule Flexible Assembly Lines

Flexible Assembly Systems - Hardware Components and Features: Basic components of a FAS.- Classification of flexible assembly systems.- Examples of industrial installations.- Issues in Design, Planning and Scheduling of Flexible Assembly: FAS design issues.- Network design for material flow systems.- Design for assembly.- Assembly planning.- Planning and scheduling.- Loading and Routing Decisions in Flexible Assembly Systems: Description of a flexible assembly system.- Optimization of station workloads and product movements.- Design and balancing of flexible assembly lines.- Numerical examples.- Simultaneous loading and routing.- Sequential loading and routing.- Loading and Routing Decisions with Assembly Plan Selection: Simultaneous loading, routing and assembly plan selection in a general flexible assembly system.- Simultaneous loading, routing and assembly plan selection in a flexible assembly line.- Loading and Scheduling in Flexible Assembly Cells: Loading and scheduling in a robot assembly cell.- Loading and sequencing in printed circuit board assembly.- Production Scheduling in Flexible Assembly Lines: Flexible assembly line with limited intermediate buffers.- Flexible assembly line with no in-process buffers.- Global lower bounds for flexible flow lines with unlimited buffers.- Just-in-time scheduling of flexible assembly lines.- Multilevel scheduling of flexible assembly lines with limited intermediate buffers.- Machine and Vehicle Scheduling in Flexible Assembly Systems: Dispatching scheduling.- Machine and vehicle scheduling - a multi-level approach.- Machine and vehicle scheduling - a single-level approach.

To tackle the balancing and sequencing problems of flexible mixed model assembly lines with alternative precedence relations, If–then rules and AND/OR graphs are adopted as modelling tools to replace precedence graphs that have limitations in representing alternative precedence relations. Mixed integer linear programming (MILP) and constraint programming (CP) models are established respectively. Moreover, an iterative decomposition method is developed to deal with large-sized problems. Computational experiments on different scales are carried out to test those methods. The computational results reveal that the performance of CP is better than MILP especially when more OR relations exist. And the iterative decomposition method outperforms MILP and CP in terms of solution quality and time.

With the combination of the extension method and multi-agent, the assemble process of the motor and its subassembly was analyzed to build the corresponding Agent and multi-Agent System model; The architecture of the flexible assembly line was established based on the established model. Finally, with the technology of fieldbus and industrial control, a flexible assembly line control system was developed based on the Profibus-DP and it provided the effective solution for the combination of theory and practical application and the applicable model for the establishment of the architecture of the flexible assembly line.

A heuristic search algorithm is given that determines and resolves the Hamiltonian circuit problem in directed graphs. The heuristic information of each vertex is a set composed of its possible path length values from the starting vertex, which is obtained by the path length extension algorithm. A detailed analysis of algorithm examples shows that the heuristic algorithm can greatly reduce the number of processing nodes compared to the backtracking algorithm without information; meanwhile, the algorithm’s time complexity is related to the number of loops in the directed graph. If a directed graph G(V, E) only contains loops that contain the starting point, then the Hamiltonian problem of G can be determined in polynomial time. The algorithm is implemented using C++ and Python programming, and all of the test graphs are generated by the random graph algorithm. The experiments show that the heuristic algorithm can reduce the number of extended nodes by at least 10% in directed random graphs with no or only a few loops. This heuristic algorithm can save time in applications that perform tasks while extending nodes because it reduce the number of extended nodes.

A scheduling problem of flexible mixed-flow assembly line with non-tight operations priority constraints is studied in this paper. A mathematic model is established to minimize the makespan. Considering the products assembly sequence and the assignment and sequence of product operations on each workstation, a genetic algorithm combined with neighborhood search strategy is designed. The optimal parameter configuration of the algorithm is found through the calculation experiments of different scale problems, and the effectiveness of the proposed algorithm is verified.

Differential Evolution (DE) algorithm is a heuristic random search algorithm based on the group difference, and it is also an optimization algorithm which processes random search in the continuous space with actual number vector coding. In uranium ore classification, its impossible to know in advance the number of best features to select. This paper puts forward a new algorithm named Variable-number Differential Evolution (VDE) algorithm, and applies it to selecting the best features of hyperspectral data. Then applies k-nearest neighbor, decision tree, naïve bayes, naïve bayes tree and support vector machine algorithm on the newly obtained data set only containing the selected features, records average accuracy by 10-fold cross-validation. The results show that new algorithm can improve the accuracy of classification compared with genetic algorithm (GA) and original DE algorithm.

With the proliferation of Web services and the evolution towards the Semantic Web comes the opportunity to automate various Web services tasks. A number of approaches have been proposed to tackle the problem of automatic web service composition. Most of them are inspired by the researches in AI planning. As heuristics plays a key role in the promotion of planning efficiency, the selection of heuristic mechanism is very important. In this paper, we propose the conception of composition distance, and propose a heuristic bidirectional search algorithm based on composition distance. The most contribution of this paper is : (1)propose the conception of composition distance; (2)a heuristic bidirectional search algorithm. The algorithm we proposed is effective and efficiency when applied in web service composition engine.

In today's highly competitive market, manufacturing companies compete in order to achieve a superior customer response and significant cost savings. From this perspective, the lexicographic bottleneck assembly line balancing problem is recently introduced to the literature in order to implement more reliable assembly lines through increasing the quality of balance among the most heavily loaded workstations. The purpose of this work is to integrate the advantage of the flexible assembly lines through considering variety of resource alternatives for executing each task with the concept of the lexicographic bottleneck assembly line balancing. Accordingly, a new mathematical model called Lexicographic Bottleneck Mixed-Model Flexible Assembly Line Balancing Problem (LB-MFALBP) is formalized for the first time in the literature. In addition, an exact solution is proposed for optimally solving small instances using a commercial solver in a reasonable computation time.

Fixtures are used to position and hold parts for a series of assembly operations. In automotive body assembly, these fixtures conventionally have been dedicated, therefore they must be replaced whenever there are model changes in an auto body assembly plant. In recent years, however, the automotive industry has been changing from high volume to small-to-medium volume production per model with an increasing number of models because customer tastes are diversifying. To cope with this change, auto companies need to be capable of producing a variety of models in small-to-medium volume, and they rely on flexible assembly lines and flexible fixtures. These flexible fixtures use robots as programmable fixture elements so that they can be reprogrammed for different stamped sheet metal parts. When designing flexible fixtures, fixture designers need to be concerned with fixture workspaces for a set of different stampings. However, existing fixture design methods address the fixturing of one stamping only. This paper presents a system that fixture designers can use to synthesize flexible fixture workspaces for a set of different stampings. Based on circular workspaces for flexible fixture robots, this system finds optimal workspace sizes and centers on a fixture base plate with a graphical display for visual checking. This system is simple to use and produces results quickly.

Manufacturing control systems are facing difficulty on adopting agility in today’s dynamic environment. Much research has been conducted on the use of multi-agent systems to facilitate this transition. In our previous work, a radio frequency identification–enabled multi-agent-based manufacturing control system was introduced for flexible manufacturing systems. In that control system, a direct coordination mechanism coordinates the agents. However, the decision-making response of the control system to disturbances was low and caused the agents to spend more time on processing messages than doing the actual job. Thus, in this article, we propose an indirect coordination mechanism based on ant colony intelligence aiming to improve the self-organization and processing time of the system. The new system utilizes the stigmergy mechanism for cooperation among the agents. Furthermore, ant agents are created by the existing agents to enable communication among them. The proposed new mechanism was implemented in a flexible assembly line. The simulation results of a case study considering shop floor problems indicates, for most performance measures, that the radio frequency identification–enabled multi-agent-based manufacturing control system integrated with indirect coordination mechanism performs better in comparison with the radio frequency identification–enabled multi-agent-based manufacturing control system integrated with direct coordination mechanism.

Some complexity results in cyclic scheduling

Planning of distribution substations, feeders and sectionalizing switches using heuristic algorithms

However, most heuristic algorithms are solely based on image features, due to the lack of diverse attributes of samples. Rather than rely on the existing datasets, this paper fully processes the original data. Firstly, the original videos were collected from several intelligent traffic surveillance cameras (monitoring nodes). Then, the three categories of objects in all videos were classified by a video image classifier. For each object in the critical class of cars, four attributes were identified, including ID, region of interest (ROI), sampling time and sampling position (position of sampling node). Next, the moving attitude (i.e. moving direction and speed) of each object was estimated through moving target tracking, and added to the preprocessed data. On this basis, a basic hyper-spherical hash search algorithm was created for the initial identification of similar objects. Furthermore, 93% of the objects were accurately identified through the recognition of license plate. Thereafter, a spatiotemporal correlation Bayesian network (STCBN) was established to predict the probability of each object to appear at a certain node in a period of time. Based on the probability, the heuristic factor was designed and used to enhance the basic hyper-spherical hash search algorithm. The enhancement improves the search performance, while reducing the environmental requirements of a single node. Therefore, the enhanced algorithm can be deployed effectively in edge computing systems. Our method was proved effective through experiment on a number of actual monitoring nodes.

Hybrid method integrating agent-based modeling and heuristic tree search for scheduling of complex batch processes

Heuristic search algorithm has been widely used in the fields of geographic information system, intelligent robot path planning, etc. This paper proposes a heuristic search algorithm based on artificial neural network, which is named ANN*. The architecture of the ANN* algorithm is similar to the A* algorithm, but it contains a novel heuristic function of the new design. This novel heuristic function utilizes the regression network, which is a kind of classical artificial neural network. In the ANN* algorithm, the artificial neural network is used to learn the features of massive map data and predict the path search difficulty of the map. In order to guarantee the diversity of the training data, this paper designs a random map generation framework, which is able to generate random grid maps according to the length, width and density. The experiments show that the ANN* algorithm can accomplish the task of path planning in the grid map with high quality. This paper provides a new scheme of exploring the applications of artificial neural network for heuristic search algorithm.