A Multi-Object Genetic Algorithm for the Assembly Line Balance Optimization in Garment Flexible Job Shop Scheduling

Numerous clothing enterprises in the market have a relatively low efficiency of assembly line planning due to insufficient optimization of bottleneck stations.As a result,the production efficiency of the enterprise is not high,and the production organization is not up to expectations.Aiming at the problem of flexible process route planning in garment workshops,a multi-object genetic algorithm is proposed to solve the assembly line bal-ance optimization problem and minimize the machine adjustment path.The encoding method adopts the object-oriented path representation method,and the initial population is generated by random topology sorting based on an in-degree selection mechanism.The multi-object genetic algorithm improves the mutation and crossover operations according to the characteristics of the clothing process to avoid the generation of invalid offspring.In the iterative process,the bottleneck station is optimized by reasonable process splitting,and process allocation conforms to the strict limit of the station on the number of machines in order to improve the compilation efficiency.The effectiveness and feasibility of the multi-object genetic algorithm are proven by the analysis of clothing cases.Compared with the artificial allocation process,the compilation efficiency of MOGA is increased by more than 15%and completes the optimization of the minimum machine adjustment path.The results are in line with the expected optimization effect.

Multi-Objective Optimization of Multi-Product Parallel Disassembly Line Balancing Problem Considering Multi-Skilled Workers Using a Discrete Chemical Reaction Optimization Algorithm

This work investigates a multi-product parallel disassembly line balancing problem considering multi-skilled workers.A mathematical model for the parallel disassembly line is established to achieve maximized disassembly profit and minimized workstation cycle time.Based on a product’s AND/OR graph,matrices for task-skill,worker-skill,precedence relationships,and disassembly correlations are developed.A multi-objective discrete chemical reaction optimization algorithm is designed.To enhance solution diversity,improvements are made to four reactions:decomposition,synthesis,intermolecular ineffective collision,and wall invalid collision reaction,completing the evolution of molecular individuals.The established model and improved algorithm are applied to ball pen,flashlight,washing machine,and radio combinations,respectively.Introducing a Collaborative Resource Allocation(CRA)strategy based on a Decomposition-Based Multi-Objective Evolutionary Algorithm,the experimental results are compared with four classical algorithms:MOEA/D,MOEAD-CRA,Non-dominated Sorting Genetic Algorithm Ⅱ(NSGA-Ⅱ),and Non-dominated Sorting Genetic Algorithm Ⅲ(NSGA-Ⅲ).This validates the feasibility and superiority of the proposed algorithm in parallel disassembly production lines.

High-gain planar TEM horn antenna fed by balanced microstrip line

A printed TEM horn antenna with high gain fed by balanced microstrip line is proposed. The radia- tion part of the antenna consists of two symmetrical triangular metal slice branches printed on the FR-4 substrate with 1.5 mrn thickness. The two branches are fed by balanced mierostrip line. The antenna is simulated by soft- ware CST MICROWAVE STUDIO and the equivalent adopted dipole model is proposed to describe the radia- tion characteristic of the antenna. The simulation results indicate that the frequency range is from 1.64 GHz to 5 GHz with reflection coefficient less than -6 dB, and the typical gain value is 8 dB in the operating band- width. In order to improve antenna gain without influencing the bandwidth, the length of the dielectric slab should be extended appropriately in the main radiation direction. By extending the length of the dielectric slab appropriately in the main radiation direction, the antenna gain can be improved significantly without the influ- ence on the bandwidth. Besides, a metal disc loaded in the radiation direction makes the gain in band be more stable. The prototype has been fabricated and measured in microwave anechoic chamber which is coincident with the simulation results. This antenna can be widely applied in the UWB field.

Effective Hybrid Teaching-learning-based Optimization Algorithm for Balancing Two-sided Assembly Lines with Multiple Constraints

Due to the NP-hardness of the two-sided assembly line balancing （TALB） problem, multiple constraints existing in real applications are less studied, especially when one task is involved with several constraints. In this paper, an effective hybrid algorithm is proposed to address the TALB problem with multiple constraints （TALB-MC）. Considering the discrete attribute of TALB-MC and the continuous attribute of the standard teaching-learning-based optimization （TLBO） algorithm, the random-keys method is hired in task permutation representation, for the purpose of bridging the gap between them. Subsequently, a special mechanism for handling multiple constraints is developed. In the mechanism, the directions constraint of each task is ensured by the direction check and adjustment. The zoning constraints and the synchronism constraints are satisfied by teasing out the hidden correlations among constraints. The positional constraint is allowed to be violated to some extent in decoding and punished in cost fimction. Finally, with the TLBO seeking for the global optimum, the variable neighborhood search （VNS） is further hybridized to extend the local search space. The experimental results show that the proposed hybrid algorithm outperforms the late acceptance hill-climbing algorithm （LAHC） for TALB-MC in most cases, especially for large-size problems with multiple constraints, and demonstrates well balance between the exploration and the exploitation. This research proposes an effective and efficient algorithm for solving TALB-MC problem by hybridizing the TLBO and VNS.

Optimization of assembly line balancing using genetic algorithm

In a manufacturing industry, mixed model assembly line(MMAL) is preferred in order to meet the variety in product demand. MMAL balancing helps in assembling products with similar characteristics in a random fashion. The objective of this work aims in reducing the number of workstations, work load index between stations and within each station. As manual contribution of workers in final assembly line is more, ergonomics is taken as an additional objective function. Ergonomic risk level of a workstation is evaluated using a parameter called accumulated risk posture(ARP), which is calculated using rapid upper limb assessment(RULA) check sheet. This work is based on the case study of an MMAL problem in Rane(Madras) Ltd.(India), in which a problem based genetic algorithm(GA) has been proposed to minimize the mentioned objectives. The working of the genetic operators such as selection, crossover and mutation has been modified with respect to the addressed MMAL problem. The results show that there is a significant impact over productivity and the process time of the final assembled product, i.e., the rate of production is increased by 39.5% and the assembly time for one particular model is reduced to 13 min from existing 18 min. Also, the space required using the proposed assembly line is only 200 m2 against existing 350 m2. Further, the algorithm helps in reducing workers fatigue(i.e., ergonomic friendly).

A Heuristic Method for Two-sided Assembly Line Balancing Problem

A two-sided assembly line is typically found in plants producing large-sized products. Its advantages over a one-sided line and the difficulties faced in two-sided line balancing problems were discussed. A mathematical model for two-ALB problem was suggested. A modification of the “ranked positional weight” method, namely two-ALB RPW for two-ALB problems was developed. Experiments were carried out to verify the performance of the proposed method and the results show that it is effective in solving two-sided assembly line balancing problems.

An efficient migrating birds optimization algorithm with idle time reduction for Type-I multi-manned assembly line balancing problem

Multi-manned assembly line,which is broadly utilized to assemble high volume products such as automobiles and trucks,allows a group of workers to assemble different tasks simultaneously in a multi-manned workstation.This additional characteristic of parallel operators increases the complexity of the traditional NP-hard assembly line balancing problem.Hence,this paper formulates the Type-I multi-manned assembly line balancing problem to minimize the total number of workstations and operators,and develops an efficient migrating birds optimization algorithm embedded into an idle time reduction method.In this algorithm,a new decoding mechanism is proposed which reduces the sequence-dependent idle time by some task assignment rules;three effective neighborhoods are developed to make refinement of existing solutions in the bird improvement phases;and temperature acceptance and competitive mechanism are employed to avoid being trapped in the local optimum.Comparison experiments suggest that the new decoding and improvements are effective and the proposed algorithm outperforms the compared algorithms.

Optimization of Line Configuration and Balancing for Flexible Machining Lines

Line configuration and balancing is to select the type of line and allot a given set of operations as well as machines to a sequence of workstations to realize high-efficiency production. Most of the current researches for machining line configuration and balancing problems are related to dedicated transfer lines with dedicated machine workstations. With growing trends towards great product variety and fluctuations in market demand, dedicated transfer lines are being replaced with flexible machining line composed of identical CNC machines. This paper deals with the line configuration and balancing problem for flexible machining lines. The objective is to assign operations to workstations and find the sequence of execution, specify the number of machines in each workstation while minimizing the line cycle time and total number of machines. This problem is subject to precedence, clustering, accessibility and capacity constraints among the features, operations, setups and workstations. The mathematical model and heuristic algorithm based on feature group strategy and polychromatic sets theory are presented to find an optimal solution. The feature group strategy and polychromatic sets theory are used to establish constraint model. A heuristic operations sequencing and assignment algorithm is given. An industrial case study is carried out, and multiple optimal solutions in different line configurations are obtained. The case studying results show that the solutions with shorter cycle time and higher line balancing rate demonstrate the feasibility and effectiveness of the proposed algorithm. This research proposes a heuristic line configuration and balancing algorithm based on feature group strategy and polychromatic sets theory which is able to provide better solutions while achieving an improvement in computing time.

Comparison of modelled-and remote sensing-derived daily snow line altitudes at Ulugh Muztagh,northern Tibetan Plateau

The ice cap Ulugh Muztagh in the central Kunlun Shan at the northern fringe of the Tibetan Plateau is a very isolated region with arid cold conditions. No observational, meteorological or glaciological ground truth data is available. Using the Moderate-resolution Imaging Spectroradiometer(MODIS) Level 1 radiance Swath Data(MOD02QKM) with a spatial resolution of 250 m, transient snow lines during the months of July to September in 2001 to 2014 are derived. Results are used to calibrate the physical based Coupled Snowpack and Ice surface energy and Mass balance model(COSIMA). The model runs on a representative detail region of Ulugh Muztagh(UM) on a digital elevation model with the same spatial resolution as the MODIS bands. In the absence of field observations, the model is driven solely by dynamically downscaled global analysis data from the High Asia Refined analysis(HAR). We compare remote sensing derived and modelled mean regional transient snow line altitudes in the course of consecutive summer seasons in 2008 to 2010. The resulting snow line altitude(SLA) and annual equilibrium line altitude(ELA) proxy of both methods coincide very well in their interannual variability in accordance with interannual variability of climatic conditions. Since SLAs of both methods do notconsistently agree on a daily basis a usage of remote sensing derived SLAs for model calibration in the absence of field observation data is only limitedly feasible for daily analysis. ELA approximation using the highest SLA at the end of ablation period may not be applied to UM because the negative winter mass balance(MB) is not reflected in the summer SLA. The study reveals moderate negative MB for UM throughout the modelling period. The mean regional MB of UM accounts for-523±410 mm w.e. a-1 in the modelling period. Hence UM seems not to belong to the area of the ‘Karakorum anomaly' comprising a region of positive mass balances in recent years which has its centre presumably in the Western Kunlun Shan.

Assembly Line Balancing Based on Double Chromosome Genetic Algorithm

Aiming at assembly line balancing problem,a double chromosome genetic algorithm(DCGA)is proposed to avoid trapping in local optimum,which is a disadvantage of standard genetic algorithm(SGA).In this algorithm,there are two chromosomes of each individual,and the better one,regarded as dominant chromosome,determines the fitness.Dominant chromosome keeps excellent gene segments to speed up the convergence,and recessive chromosome maintains population diversity to get better global search ability to avoid local optimal solution.When the amounts of chromosomes are equal,the population size of DCGA is half that of SGA,which significantly reduces evolutionary time.Finally,the effectiveness is verified by experiments.

A scenario relaxation algorithm for finite scenario based robust assembly line balancing

A balancing problem for a mixed model assembly line with uncertain task processmg Ume anO daily model mixed changes is considered, and the objective is to minimize the work variances between stations in the line. For the balancing problem for the scenario-based robust assembly line with a finitely large number of potential scenarios, the direct solution methodology considering all potential scenarios is quite time-consuming. A scenario relaxation algorithm that embeds genetic al- gorithm is developed. This new algorithm guarantees termination at an optimal robust solution with relatively short running time, and makes it possible to solve robust problems with large quantities of potential scenarios. Extensive computational results are reported to show the efficiency and effectiveness of the proposed algorithm.

CONCURRENT PRODUCT PORTFOLIO PLANNING AND MIXED PRODUCT ASSEMBLY LINE BALANCING

Reconfigurable products and manufacturing systems have enabled manufacturers to provide ＂cost effective＂ variety to the market. In spite of these new technologies, the expense of manufacturing makes it infeasible to supply all the possible variants to the market for some industries. Therefore, the determination of the right number of product variantsto offer in the product portfolios becomes an important consideration. The product portfolio planning problem had been independently well studied from marketing and engineering perspectives. However, advantages can be gained from using a concurrent marketing and engineering approach. Concurrent product development strategies specifically for reconfigurable products and manufacturing systems can allow manufacturers to select best product portfolios from marketing, product design and manufacturing perspectives. A methodology for the concurrent design of a product portfolio and assembly system is presented. The objective of the concurrent product portfolio planning and assembly system design problem is to obtain the product variants that will make up the product portfolio such that oversupply of optional modules is minimized and the assembly line efficiency is maximized. Explicit design of the assembly system is obtained during the solution of the problem. It is assumed that the demand for optional modules and the assembly times for these modules are known a priori. A genetic algorithm is used in the solution of the problem. The basic premise of this methodology is that the selected product portfolio has a significant impact on the solution of the assembly line balancing problem. An example is used to validate this hypothesis. The example is then further developed to demonstrate how the methodology can be used to obtain the optimal product portfolio. This approach is intended for use by manufacturers during the early design stages of product family design.

Heuristics for Mixed Model Assembly Line Balancing Problem with Sequencing

The growing global competition compels organizations to use many productivity improvement techniques. In this direction, assembly line balancing helps an organization to design its assembly line such that its balancing efficiency is maximized. If the organization assembles more than one model in the same line, then the objective is to maximize the average balancing efficiency of the models of the mixed model assembly line balancing problem. Maximization of average balancing efficiency of the models along with minimization of makespan of sequencing models forms a multi-objective function. This is a realistic objective function which combines the balancing efficiency and makespan. This assembly line balancing problem with multi-objective comes under combinatorial category. Hence, development of meta-heuristic is inevitable. In this paper, an attempt has been made to develop three genetic algorithms for the mixed model assembly line balancing problem such that the average balancing efficiency of the model is maximized and the makespan of sequencing the models is minimized. Finally, these three algorithms and another algorithm in literature modified to solve the mixed-model assembly line balancing problem are compared in terms of the stated multi-objective function using a randomly generated set of problems through a complete factorial experiment.

Assembly Line Balancing Using Fuzzy Logic: A Case Study of a Tricycle Assembly Line

The application of fuzzy logic in balancing a single model tricycle assembly line is presented in this study. MATLAB simulation software was used in the analysis of the primary and secondary data obtained from the assembly line under study. Results obtained from the study show that the efficiency of the line increased from 88.1% to 92.4%. The total idle time was also reduced by 56.5%. This indicates an improvement in the efficiency of the line, reduction of bottleneck, and even distribution of tasks along the line for the company under study.

A Modified Multi-Agent System for Simple Assembly Line Balancing

In this paper, a modified multi-agent system for assembly line balancing is proposed. Each worker in the assembly line is regarded as an agent, and two neighboring agents exchange information about the allocated tasks. To balance the workload, an agent with a smaller workload sends a request message to his/her neighboring agent, who has a larger workload, to exchange tasks between them. Without any centralized control mechanism, each agent behaves to achieve their goal, which is to balance the workload. A tabu list and cooling control are also incorporated. However, the effectiveness of the previous system is limited, and the system depends on problems to be solved. As such, a modified system is proposed. In the proposed system, the cycle time is used when considering the proposal of exchange of allocated tasks instead of the task time allocated to the neighboring workers. Also, in the proposed system, the length of tabu list is determined dynamically based on the current number of possible exchanges, and the best cycle time in the search with cooling at medium speed is recorded for the second search that is finished when the current cycle time reaches the recorded cycle time. The effectiveness of the modified system is investigated by solving problems for various conditions. The results show that the proposed system is effective regardless of the problems that are encountered.

The Bo-Tai Line:Establishing the concepts of a balanced regional development line and a national development backbone

Promoting regional coordinated development strategy is one of the important strategies in the new period of China.Faced with the reality of unbalanced and insufficient regional development in China,it is objectively necessary to construct one or more main axes supporting the coordinated and balanced development of regions to become the identification line representing the pattern of coordinated regional development.The results show that the Bo-Tai line,the northwest-southeast axis connecting Bole of Xinjiang and Taipei of Taiwan,can be built into national development backbone line and regional balanced development line,just perpendicular to Hu Line.In 2016,the area of southwest half and northeast half of Bo-Tai Line accounts for 60%:40%,while the population accounts for 45%:55%,the economic aggregate accounts for 40%:60%,the per capita GDP ratio accounts for 44%:56%,the population density ratio accounts for 38%:62%,the economic density ratio accounts for 32%:68%,and the urbanization level ratio accounts for 48%:52%.The main average indicators are gradually tending to balanced development pattern.Further analysis shows that Bo-Tai Line is a strategic shoulder pole connecting two core zones of"the Belt and Road",and is the peaceful reunification line of China's national tranquility and Taiwan's return.Bo-Tai Line is also a solid line supported and connected by comprehensive transportation channels and a Pipa type symmetrical line for the development of cities and urban agglomerations.It is the backbone of the two-way opening up and the linkage development line between land and sea.It is also an important dividing line that promotes the coordinated development of the eastern,central and western regions,and addresses the imbalance and inadequacy of regional development.Bo-Tai Line plays an irreplaceable strategic role in promoting the coordinated and balanced regional development.It is suggested that the construction of Bo-Tai Line should be included in the national development strategy,and the development strategic plan of Bo-Tai Line should be formulated to fully release the multiple potential functions.We should build three strategic support points:the northwest endpoint,the central strategic node and the southeast endpoint;carry out a comprehensive scientific investigation of the Bo-Tai Line,and strengthen the scientific cognition and publicity;promote China's development in a higherlevel,higher-quality,more coordinated,safer and more civilized direction.Let Chinese know about the Bo-Tai Line,let the world know about the Bo-Tai Line,and let the Bo-Tai Line truly become the backbone of the great rejuvenation of the Chinese nation.

Strategic Robust Mixed Model Assembly Line Balancing Based on Scenario Planning

Assembly line balancing involves assigning a series of task elements to uniform sequential stations with certain restrictions. Decision makers often discover that a task assignment which is optimal with respect to a deterministic or stochastic/fuzzy model yields quite poor performance in reality. In real environments, assembly line balancing robustness is a more appropriate decision selection guide. A robust model based on the α worst case scenario is developed to compensate for the drawbacks of traditional robust criteria. A robust genetic algorithm is used to solve the problem. Comprehensive computational experiments to study the effect of the solution procedure show that the model generates more flexible robust solutions. Careful tuning the value of α allows the decision maker to balance robustness and conservativeness of as- sembly line task element assignments.

A survey on assembly lines and its types

Assembly lines are useful for mass production of standard as well as customized products. Line balancing is an important issue, in this regard an optimal or near optimal balance can provide a fruitful savings in the initial cost and also in the running cost of such production systems. A survey of different problems in different types of assembly lines and some of the critical and on going research areas are highlighted here. The provided research information is momentous for the research community in assembly line area to proceed further in the presented issues of assembly lines.

Pareto lexicographic a-robust approach and its application in robust multi objective assembly line balancing problem

Robustness in most of the literature is associated with rain-max or min-max regret criteria. However, these criteria of robustness are conservative and therefore recently new criteria called, lexicographic a- robust method has been introduced in literature which defines the robust solution as a set of solutions whose quality orjth largest cost is not worse than the best possible jth largest cost in all scenarios. These criteria might be significant for robust optimization of single objective optimization problems. However, in real optimization problems, two or more than two conflicting objectives are desired to optimize concurrently and solution of multi objective optimization problems exists in the form of a set of solutions called Pareto solutions and from these solutions it might be difficult to decide which Pareto solution can satisfy rain-max, min-max regret or lexico- graphic a-robust criteria by considering multiple objectives simultaneously. Therefore, lexicographic a-robust method which is a recently introduced method in literature is extended in the current research for Pareto solutions. The proposed method called Pareto lexicographic a-robust approach can define Pareto lexicographic a-robust solu- tions from different scenarios by considering multiple objectives simultaneously. A simple example and an application of the proposed method on a simple problem of multi objective optimization of simple assembly line balancing problem with task time uncertainty is presented to get their robust solutions. The presented method can be significant to implement on different multi objective robust optimization problems containing uncertainty.