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Intelligent manufacturing automation is a future trend, and optimizing production resource control using blockchain technology is a meaningful research topic. Existing studies have limitations, such as varying PSCO-PC models and insufficient flexibility in simulation models. This paper proposes a novel blockchain-based PSCO-PC strategy for intelligent manufacturing. It details the PSCO-PC model, improving the matching rationality and applicability of simulation system functions. The adaptive difficulty concept is introduced to address data throughput and consensus mechanism issues. Calculation steps for solving the optimal package revenue of PSCO matching records are provided. Experimental results confirm the effectiveness of the proposed simulation model and PSCO-PC strategy. [ABSTRACT FROM AUTHOR]

With the rapid development of the industry sector, the assembly line has also experienced development, whose rationality determines the production efficiency of industrial production. In this paper, in order to address the balancing issue of assembly lines for industrial production, a combinatorial optimization method is proposed for the optimization and implementation of the assembly line based on the improved genetic algorithm (GA) and system simulation. By being applied to the assembly line of a company's chiller, our method is proved practical and effective. [ABSTRACT FROM AUTHOR]

This paper describes the use of genetic algorithms (GA) for solving the facility layout problem (FLP) within manufacturing systems' design. The paper considers a specific heuristic layout planning method, known as the modified triangle method. This method seeks for an optimal layout solution based on the degrees of flows between workstations. The search for an optimal solution is extremely time-consuming and not suitable for larger systems; therefore we have developed a system based on evolutionary computation. Our paper presents a system, based on GA, and the results obtained regarding several numerical cases from the literature. We propose the usage of this system by presenting numerous advantages over other methods of solving FLP for problem representation and evolutionary computation for solution search. [ABSTRACT FROM AUTHOR]

This paper attempts to overcome the defects of bottleneck recognition and scheduling optimization in open production line. For this purpose, the author analysed the impact mechanism of external disturbances and system configuration changes on the production line, and put forward a multibottleneck identification model for production line through computer simulation. Then, the proposed model was applied to optimize the scheduling of open production line. Specifically, the bottlenecks of production line were identified based on hierarchical clustering and multi-attribute decision-making, aiming to overcome the small candidate set and low accuracy of traditional bottleneck identification algorithms. The measured results show that the proposed algorithm has clear primary and secondary logics; the number of main bottleneck clusters decreased with the increase in the order; the number of machines in the main bottleneck cluster changed nonlinearly. The traditional genetic algorithm (GA) was improved in three aspects: the local optimum trap was avoided by enhancing population diversity; the iteration speed was accelerated with the introduction of adaptive crossover operator and genetic operator; without sacrificing the computing speed, the convergence quality was guaranteed through the addition of multivariate competition algorithm. The research findings provide new insights into the efficient operation of production line. [ABSTRACT FROM AUTHOR]

A systematic procedure for modeling, simulation and optimal tuning the parameters of a Thyristor Controlled Series Compensator (TCSC) controller, for the power system stability enhancement is presented in this paper. For the simulation purpose, the model of single-machine infinite bus (SMIB) power system with TCSC controller is developed in MATLAB/SIMULINK. The design problem of TCSC controller is formulated as an optimisation problem and genetic algorithm (GA) is employed to search for the optimal TCSC controller parameters. By minimizing a time-domain based objective function, in which the oscillatory rotor speed deviation of the generator is involved; stability performance of the power system is improved. The results obtained from simulations validate the effectiveness of proposed modelling and tuning approach for power system stability improvement. The simulation results also show that the proposed TCSC controller is effective in damping a range of small disturbance conditions in the power system. [ABSTRACT FROM AUTHOR]

In this paper we address the problem of automatically computing a set of views over a simulated three dimensional environment. The viewing system aims at, for each moment, supplying the user with the most pertinent information in order to allow a good understanding of the evolving environment. Our approach relies on an innovative optimization architecture that enables intelligent optimization techniques based on simulated annealing and genetic algorithms. Reported experiments were performed in urban rescue scenarios from the RoboCup Rescue Domain. We outline the possible extension of the proposed architecture to other visualization problems and argue on how several problems within the fields of Visualization and Rendering can benefit from it. [ABSTRACT FROM AUTHOR]

This paper applies the non-dominated sorting genetic algorithm (NSGA) to the design of non-compact flow shop scheduling plan, and successfully solves the multi-objective optimization problem considering process connection. Specifically, an NSGA-based scheduling strategy was developed after analysing the features of the non-compact flow shop in manufacturing enterprises, and an improved algorithm was created for the multi-objective optimization of non-compact flow shop scheduling considering process connection. The research results show that: the improved NSGA is a desirable way to solve the multi-objective optimization of non-compact flow shop scheduling, as it ensures the population diversity and guarantees the evolution effect; this algorithm is more realistic than traditional algorithms, which overlooks the process connection; the case simulation and analysis reveal that the established multi-objective scheduling model for non-compact flow shop enjoys good adaptability. The research finding carries profound theoretical and practical significance for enterprises, e.g. improving the scheduling of non-compact flow shop, production efficiency and response to market situations. [ABSTRACT FROM AUTHOR]

Starting from the description and the classification of scheduling problems, this paper studies the problem of scheduling n jobs on a single machine in order to minimize the number of late jobs. Each job has a release time, a certain processing time and a due time. Taking into consideration all the aspects involved in scheduling, this specific case of problem is one of the most important because of its applicability on the engineering field, many solutions being proposed for its solving. By combining priority rules with genetic algorithms, this paper offers a hybrid solution for solving this problem. [ABSTRACT FROM AUTHOR]

This paper presents a novel heuristic method for machine layout optimisation, developed in the course of an internal factory logistics optimisation project. The method is developed from a force-directed graph drawing algorithm, and integrates random permutations using simulated annealing to avoid local minima. The method was verified and validated with a discrete event simulation (DES) model of a furniture development factory consisting of 140 machines. The DES model was developed for manufacturing system analysis as well as design and testing of optimisation methods. The main optimisation goal was reduction of transport costs by minimising the total distance the products travel between the machines. The optimisation problem extends the quadratic assignment problem (QAP) by allowing arbitrary granularity of locations, facility sizes and fixed facilities. The resulting method can be used to solve a wider range of problems by altering the optimisation function or adding new feasibility conditions. [ABSTRACT FROM AUTHOR]

The paper deals with the problems of a mathematical and computing model designing of the defined problem based on isomorphism and homomorphism representation, the essence and the principle of genetic algorithms as well as their application to the solution of selected optimization problems. [ABSTRACT FROM AUTHOR]

Single source capacitated facility location problems (SSCFLP) are basic location-allocation models used in the optimal design of supply chain, computer network and transmission power, amongst others. While genetic algorithm (GA) has been successfully applied to many combinatorial optimization problems, it has limited success when applied to solving SSCFLP. This paper proposes a GA solution which adopts an integer-based chromosome encoding approach using roulette wheel selection to allocate the alleles in the chromosome. A case study is conducted which shows that the algorithm is capable of solving the problem within short computational time. [ABSTRACT FROM AUTHOR]

Research of efficiency of multi-pass turning processes has significant practical importance. Non-traditional optimization techniques such genetic algorithms (GA), artificial neural networks (ANN) and PSO optimization are increasingly used to solve optimization problems. This paper presents a new multi-objective optimization technique, based on ant colony optimization algorithm (ACO), to optimize the turning processes. Three conflicting objectives, production cost, operation time and cutting quality are simultaneously optimized. An objective function based on maximum profit in operation has been used. The proposed approach uses adaptive neuro-fuzzy inference system (ANFIS) system to represent the manufacturer objective function and an ant colony optimization algorithm (ACO) to obtain the optimal objective value. New evolutionary ACO is explained in detail. [ABSTRACT FROM AUTHOR]

JaamSim is a prominent, discrete-event simulator with an established and fast growing community of users. To the authors' knowledge, no simulation optimisation package was available for JaamSim up to now. For the purposes of this research, we developed the open-source software JSOptimizer that can be used to optimise simulation models of complex engineering systems built with JaamSim. The proposed tool utilises the jMetal framework, a well-known and validated library of meta-heuristic optimisation algorithms. The contribution of this article is twofold. First, we present the most important aspects of the proposed software JSOptimizer. Secondly, we examine a novel, multiobjective problem pertaining to a stochastic manufacturing system which involves production control and job routing decisions. Several instances of the optimisation problem are solved and the resulting local non-dominated sets are compared under various performance metrics by utilizing the functionalities of JSOptimizer. This investigation also serves as a proof of concept for the proposed software's applicability. [ABSTRACT FROM AUTHOR]

The effects of the spiral line for pick arrangement on the cutting load of a boom type roadheader's cutting head were investigated. For this purpose, cutting heads with equal and unequal pitch angle and various numbers of spiral lines were designed for the same cutting head body. The cutting head with unequal pitch angle of spiral lines was specifically designed to avoid tool-holder overlap at the top section without adjustments and reduce the manufacturing difficulties. The cutting process of different cutting heads were simulated by finite element method using ANSYS/LS-DYNA and the time history curve of the traversing force, vertical force, axial force, and resultant force on the cutting head were obtained. The results indicate that the load stability of the cutting head with unequal pitch angle was worse than the equal pitch angle cutting head. For cutting heads with various numbers of spiral lines, the head with 3 spiral lines shows the best performance, considering the force values and fluctuations of the cutting head. The analysis provides a reliable basis for optimization of the design of boom type roadheader cutting heads. [ABSTRACT FROM AUTHOR]

Flexible job-shop scheduling problem (FJSP) in the field of production scheduling presents a quite difficult combinatorial optimization problem. Machines are mostly considered to be the only resource in many research projects dealing with FJSP. In actual production, there are many other factors which influence production scheduling, such as transportation, storage and detection. If machines are considered to be the only resource, the problem may not be in accord with the actual production. Thus, in order to make FJSP more in line with the real production situation, machines, warehouses, vehicles and detection equipment are all considered to be the scheduled resources simultaneously due to the shortage of flexible job shop scheduling problem in resources. A new mathematical model for a multiresource flexible job-shop scheduling problem (MRFJSP) is proposed. The constraints of the model are presented. The makespan is the main target which will be minimized. A genetic algorithm which includes elitist strategy is proposed to solve the MRFJSP. Due to the complexity of MRFJSP, each key module of the genetic algorithm is redesigned. Finally, the model and algorithm are proved through an application case. [ABSTRACT FROM AUTHOR]