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In the mixed-model assembly line balancing and sequencing problem (MALBSP), workstations are assumed to be constantly available. The failure of any workstation will make the entire assembly line stop working. Preventive maintenance (PM) is a way to maintain the workstation before its failure, reduce unexpected downtime, and prolong its useful life. Previous studies have considered PM scenarios (PMS) in the simple and U-shaped assembly line to improve production efficiency and smoothness effectively, but not in the mixed-model assembly line. This paper fills this research gap, and the MALBSP considering PMS (MALBSP_PMS) is studied in this paper. A mixed-integer linear programming model is proposed to minimize makespan and task alteration. A migrating birds optimization algorithm is improved (IMBO) to obtain well-distributed Pareto frontier solutions. This algorithm designs a restart mechanism and an intra-population crossover operator to avoid falling into the local optimal and enhance its searchability. Experimental results demonstrate the effectiveness of two improvements and the IMBO algorithm. In addition, a real-world case study is introduced to illustrate the importance of considering PM scenarios in MALBSP. [ABSTRACT FROM AUTHOR]

Seafloor real-time positioning is important for the instantaneous detection of seafloor crustal motion, seismic activities, hydrological rapid variations and rapid geodetic datum updates. Current GNSS-Acoustic (GNSS-A) seafloor positioning usually utilizes batch processing of long-term observations in the postprocessing mode. Seafloor real-time positioning can be achieved using sequential processing of the epoch-wise observations. We propose the sequential GNSS-A seafloor point positioning method with modeling of the sound speed variation in the kinematic survey. We propose real-time modeling of the sound speed variation using oceanography analysis data and we then calculate the random walk (RW) process noise of the acoustic nadir total delay (NTD) caused by the sound speed variation. The experiments conducted in the South China Sea and Japan Trench validate the method performance in terms of epoch-wise positioning accuracy, high-resolution sound speed variation, and filter convergence time. The difference between the estimated sound speed and the in situ sound velocity profiles was 0.128 m/s root mean square. The vessel track of the line and circle combination performs best with a high positioning accuracy and a short convergence time. The position in real-time sequential processing with the modeled NTD RW process noise converged to a 3D range of 0.125 m from the static post-determined position. The a posteriori residual of the acoustic travel time observations was equivalently 0.270 m in range. These findings can improve the temporal resolution of the GNSS-A positioning and oceanography. [ABSTRACT FROM AUTHOR]

While solving the shunting scheduling of EMU first-level maintenance (SSEFM), most existing literature assumed a single maintenance route for all trains and considered only a through depot. It neglects the problem-specific characteristics in terms of varied maintenance routes and a stub-end depot, causing the infeasibility of the generated schedule in such particular circumstances. Therefore, the SSEFM problem with flexible maintenance routes in a stub-end depot with a transversal yard configuration is considered in this work. First, a multi-objective mixed-integer linear programming (MILP) model is formulated to maximize the reservation time in the storage area, and minimize the overstay time in the cleaning and inspecting areas. The relationship between constraints including flexible maintenance routes, train shunting conflicts, track occupation conflicts, and train arrival/departure times, are coordinated. Subsequently, a heuristic-based enhanced particle swarm optimization algorithm (EPSO) with two improvements is proposed to tackle this NP-hard problem. Specifically, three heuristic rules about the depth-first operation track allocation, the conflict-free bottleneck track allocation, and the right-shift track occupancy repair are designed to ensure the feasibility of the shunting schedule. Accordingly, a three-level decoding mechanism is designed to achieve a near-optimal shunting schedule with great train and route sequences. Two improvements on crossover and mutation operators are developed to enhance the exploration and exploitation ability. Finally, a real-world instance in China is solved to verify the effectiveness and efficiency of the proposed model and algorithm. Experimental results show that EPSO is relatively more effective than all the compared algorithms. [ABSTRACT FROM AUTHOR]

The collaborative robots (cobots) are increasingly being utilized in industries due to the advancement in the field of robotic technology and also due to the increase in labor costs. The cobots on the assembly line can be utilized to complete the tasks independently or assist the workers to complete the tasks. This study considers the U-shaped assembly line balancing problem with cobots, where several cobots with different purchasing costs are selected under the budget constraint. Three mixed-integer programming models are formulated to optimize the cycle time, and the built models are capable of solving the small-sized instances optimally. Two algorithms, artificial bee colony algorithm and migrating bird optimization algorithm, are developed and improved to tackle the large-sized instances, where new encoding scheme and decoding procedure are developed for this new problem. The computational tests demonstrate that the utilization of collaborative robots reduces the cycle time effectively in the assembly line. The comparative study on a set of instances shows that the proposed methodologies obtain competing performance in comparison with other 12 implemented algorithms. [ABSTRACT FROM AUTHOR]

Disassembly is the first and vital step in recycling and remanufacturing end-of-life products. Disassembly lines are utilized frequently due to high productivity and suitability. This research studies the disassembly line balancing problem on the U-shaped disassembly lines, which have higher flexibility than the traditional straight disassembly lines. A mixed-integer linear programming (MILP) model is developed to formulate the AND/OR precedence relationships with the objective of minimizing the number of stations. This model is also extended to a mixed-integer nonlinear programming model to optimize four objectives. To tackle this NP-hard problem effectively, a two-phase artificial bee colony algorithm and a bee algorithm are proposed and improved. In these algorithms, the first phase selects the stations with less loads on the last two stations for the purpose of achieving the optimal number of stations. The second phase hierarchically optimizes multiple objectives to achieve better line balances. Case studies show that the proposed MILP model obtains optimal solutions in terms of station number for the small-size instances, and the U-shaped disassembly lines obtain better fitness values than the straight disassembly lines. The comparative study demonstrates that the proposed methodologies perform competing performances in comparison with other 13 re-implemented algorithms, including tabu search algorithm, iterated local search algorithm, genetic algorithm, particle swarm optimization, three artificial bee colony algorithms and the original bee algorithm. [ABSTRACT FROM AUTHOR]

High-resolution multi-beam/single-beam bathymetric data and seismic profiling data from the latest surveys are used to map and interpret the detailed seafloor geomorphology of the western region of the North Yellow Sea (NYS), China. The mapping area covers 156 410 km2, and incorporates a flat shelf plain, subaqueous accumulation shoals, tidal scouring troughs, and tidal sand ridge groups. Offshore areas with water depths less than 50 m in the western region of the NYS are mainly covered by thick, loose sediments, forming wide spread accumulation geomorphological features; these include the Liaodong Peninsula subaqueous accumulation system containing shoals and rugged scouring troughs, and the large mud wedge of the Shandong Peninsula. In the central part of the NYS, there is a relatively flat residual shelf plain with coarser sediment deposits. This flat shelf plain has a water depth larger than 50 m and a thin layer of sediment, on which there is a large pockmark field caused by seafloor seepage. These geomorphological structures indicate that modern sedimentary processes are the main driving force controlling the sculpture of the current seafloor surface landform. Extensive strong tidal current systems and abundant sediment sources provide the critical external forces and essential conditions for the formation of seafloor geomorphology. The tectonic basement controls the macroscopic morphological shape of the NYS, but is reflected very little in the seafloor geomorphic elements. Our results provide a detailed seafloor geomorphological map of the western region of the NYS, an area that has not previously mapped and also provide a scientific framework for further research into offshore seafloor geomorphology, shelf sedimentary processes, and submarine engineering construction in this region. [ABSTRACT FROM AUTHOR]

In this paper, flexible preventive maintenance (PM) activities are incorporated into two-stage assembly flow shop scheduling where m dedicated machines in the fabrication stage and one machine in the assembly stage. The operational status of each machine is described by a continuous variable, maintenance level. The maintenance level value is inversely proportional to the processing time. Once a PM activity is performed, this value will return to the initial value. Different from the PM at fixed predefined time intervals, flexible PM can be carried out at any time point, but the maintenance levels are not less than 0. Hence, a MILP model with maintenance level constraints is formulated to minimize the total completion time and maintenance time. Regarding the methods, a latest PM decision strategy is proposed to determine the execution time of PM activities. This new strategy is embedded into 15 constructive heuristics and 7 meta-heuristics (three variants of iterated local search, three variants of Q-learning-based ant colony system with local search and a Q-learning-based hyper-heuristics) to address this new problem. The final experimental analysis demonstrates the significance of the integrated model and the effectiveness of the proposed constructive heuristics and meta-heuristics. [ABSTRACT FROM AUTHOR]

Industries are increasingly looking for opportunities at utilizing collaborative robots in assembly lines to perform the tasks independently or assist the human workers due to the advancement of industry 4.0 technologies. Purchasing cost is one of the important factors to be considered by production managers, while designing or redesigning assembly line when collaborative robots are being utilized. Several objectives are to be optimized in an assembly line balancing problem and optimizing line efficiency along with purchasing cost sometimes results in conflicting situation. This paper presents the first study to tackle the cost-oriented assembly line balancing problem with collaborative robots, where several different types of collaborative robots with different purchasing costs are available and selected. A multi-objective mixed-integer programming model is developed to minimize the cycle time and the total collaborative robot purchasing cost. The multi-objective migrating bird optimization algorithm is developed to obtain a set of high-quality Pareto solutions. This algorithm utilizes the fast non-dominated sorting approach to update the population and develops a restart mechanism to select one solution in the permanent Pareto archive to replace the abandoned solution which remains unchanged for several iterations. The computational study validates that the utilization of the multi-objective model is reasonable and developed algorithm produces competing performance in comparison with multi-objective non-dominated sorting genetic algorithm II, multi-objective simulated annealing algorithm and two multi-objective artificial bee colony algorithms. [ABSTRACT FROM AUTHOR]

Two-sided assembly lines are widely utilized to assemble large-sized products such as cars and trucks. Recently, these types of assembly lines have been applied to assemble different types of products due to a large variety of customer demands and strong market competition. This paper presents two simple local search methods, the iterated greedy algorithm and iterated local search algorithm, to deal with type I mixed-model two-sided assembly line balancing problems. These two algorithms utilize new precedence-based local search functions with referenced permutation and two neighborhood structures to emphasize intensification while preserving high search speed. Additionally, these local search methods are enhanced by utilizing the best decoding scheme amongst nine candidates and a new station-oriented evaluation to guide the search direction. New lower bound calculations are also presented to check the optimality of the achieved solutions. Eleven recent and high-performing metaheuristic algorithms are re-implemented to test the performance of the proposed algorithms. A comprehensive study on a set of benchmark problems demonstrates the advantages of the improvements and the superiority of the two proposed methods. Experimental results show that the proposed algorithms obtain 23 new upper bounds compared with two recently published algorithms, among which 19 cases are proven to be optimal for the first time. [ABSTRACT FROM AUTHOR]

The fast and accurate estimation of makespan is essential for the determination of the delivery date and the sustainable development of the enterprise. In this paper, a high-quality training dataset is constructed and an adaptive ensemble model is proposed to achieve fast and accurate makespan estimation. First, both the logistics features extracted by the Pearson correlation coefficient and the new meaningful nonlinear combination features dug out by gene expression programming are first involved in this paper for constructing a high-quality dataset. Secondly, an improved clustering with elbow criterion and a resampling operation are applied simultaneously to generate representative subsets; and correspondingly, several back propagation neural network (BPNN) with the architecture optimized by genetic algorithm are trained by these subsets respectively to generate effective diverse learners; and then, a K-nearest neighbor based dynamic weight combination strategy which is sensitive to current testing sample is proposed to make full use of the learner's positive effects and avoid its negative effects. Finally, the results of effective experiments prove that both the newly involved features and the improvements in the proposed ensemble are effective. In addition, comparison experiments confirm that the proposed enhanced ensemble of BPNNs outperforms significantly the prevailing approaches, including single, ensemble and hybrid models. And hence, the proposed model can be utilized as a convenient and reliable tool to support customer order acceptance. [ABSTRACT FROM AUTHOR]

In this study, to meet the need for accurate tidal prediction, the accuracy of global ocean tide models was assessed in the South China Sea (0°–26°N, 99°–121°E). Seven tide models, namely, DTU10, EOT11a, FES2014, GOT4.8, HAMTIDE12, OSU12 and TPXO8, were considered. The accuracy of eight major tidal constituents (i.e., Q1, O1, P1, K1, N2, M2, S2 and K2) were assessed for the shallow water and coastal areas based on the tidal constants derived from multi-mission satellite altimetry (TOPEX and Jason series) and tide gauge observations. The root mean square values of each constituent between satellite-derived tidal constants and tide models were found in the range of 0.72–1.90 cm in the deep ocean (depth>200 m) and 1.18–5.63 cm in shallow water area (depth<200 m). Large inter-model discrepancies were noted in the Strait of Malacca and the Taiwan Strait, which could be attributable to the complicated hydrodynamic systems and the paucity of high-quality satellite altimetry data. In coastal regions, an accuracy performance was investigated using tidal results from 37 tide gauge stations. The root sum square values were in the range of 9.35–19.11 cm, with the FES2014 model exhibiting slightly superior performance. [ABSTRACT FROM AUTHOR]

Exact methods have shown advanced and promising performance in solving the simple assembly line balancing problem, known as NP-hard. This research investigates the impact of various structural parameters on the performance of exact methods, including branching methods, search direction, method to achieve upper bounds, utilized lower bounds, utilized dominance rules and search strategy. In accordance with the structural parameter evaluation, utilized dominance rules and search strategy have shown the most important effect on the exact methods' performance. This research also improves and re-implements three well-known exact methods [i.e., SALOME, bounded dynamic programming (BDP) heuristic and branch, bound and remember (BBR) algorithm] using effective parameters. Computational study demonstrates that the utilization of high-performance structural parameters enhances the performance of exact methods by a significant margin. The re-implemented BBR method with proper parameters shows clear superiority over all the published exact methods and might be regarded as the state-of-the-art exact methodology. [ABSTRACT FROM AUTHOR]

U-shaped assembly lines have been popularly adopted in electronics and appliances to improve their flexibility and efficiency. However, most past studies assumed that the processing time of each task is fixed and hence just considered the task allocation but ignored worker assignment. In this paper, the processing time of each task depends on the workers and then the cooperative optimization of task allocation and workers assignment is considered in U-shaped assembly line balancing problems to optimize the cycle time. Later, an enhanced migrating birds optimization algorithm (EMBO) is proposed to solve it. In the EMBO algorithm, since this new problem has two subproblems: task allocation and worker assignment, the prevent work designs two neighborhood structures to improve the leader and following birds. Furthermore, the temperature acceptance criteria, to judge whether the neighbor replaces current following bird, are developed to ensure the diversity of population and avoid being trapped in the local optimum. And a competitive mechanism is introduced to increase the probability of the promising birds locating in the front of the line. The proposed algorithm is compared with other well-known algorithms in the literature, and the numerical results demonstrate that the proposed algorithm outperforms other algorithms. [ABSTRACT FROM AUTHOR]

This paper investigated the quality of site-specific surface temperature and surface pressure data in the coastal regions of China, which were interpolated from the European Centre for Medium-Range Weather Forecast Interim reanalysis (ERA-Interim), Japanese 55-year Reanalysis Project (JRA-55), and the National Centers for Environmental Prediction Final (NCEP FNL) reanalysis surface meteorological datasets as well as from the new Global Pressure and Temperature (GPT2) model data. The measured temperature and pressure along with the collocated GPS data from 2014 were collected from 25 observation stations evenly located in the region. Compared with the actual meteorological observations, the performances of the interpolated data from three reanalysis datasets differ marginally, with the root mean square errors (RMSEs) of the interpolated surface temperature and pressure less than 2.4 K and 1.6 hPa, respectively; however, the RMSEs of the surface temperature and pressure interpolated from the GPT2 model were 3.0 K and 4.2 hPa, respectively. Data based on GPS PWV products that used the meteorological parameters interpolated from three reanalysis data were very close to those of meteorological observations, with biases within ± 0.4 mm and RMSEs below 0.5 mm in most areas, and the RMSE of PWV using the GPT2 model interpolation data was superior by 2 mm. The measurement of GPS PWV using the interpolated reanalysis meteorological data also compared well with radiosonde observations, with RMSE between them tending to increase with a decrease of the GPS station's latitude. However, the GPS PWV based on the interpolated data could not reflect the true change in water vapor during typhoon events. [ABSTRACT FROM AUTHOR]

A multi beam sonar survey is carried out in the continental slope of the Taixinan Basin to obtain submarine topographic and water column data. The data are processed to obtain water column images. Anomalous water column images, displaying plume characteristics, are found in gas hydrate enriched areas in the Taixinan Basin. This indicates the presence of natural gas resources in the Taixinan Basin. The multibeam sonar system is shown to provide an accurate and effective approach for detecting sub-sea gas hydrate. [ABSTRACT FROM AUTHOR]

Robotics are extensively utilized in modern industry to replace human labor and achieve high automation and flexibility. In order to produce large-size products, two-sided assembly lines are widely applied, where robotics can be employed to operate tasks on workstations. Since the applied traditional optimization methods are limited, the current work presented a new discrete cuckoo search algorithm to solve the two-sided robotic assembly line balancing problem. The original cuckoo search algorithm was modified by employing neighbor operations. Furthermore, a new procedure to generate individuals to replace the abandoned nests was developed to enhance the intensification. Since the considered problem has two subproblems, namely the robot allocation and assembly line balancing, the present work extended the cuckoo search algorithm to cooperative coevolutionary paradigm by dividing the cuckoos into two sub-swarms, each addressing a subproblem. In order to emphasize the exploration, a restart mechanism was employed. The proposed discrete algorithm’s evolution process and convergence were compared with another two popular optimization algorithms, namely the genetic algorithm and particle swarm optimization algorithm. Computational study on the proposed algorithms and other five recent algorithms along with statistical analysis demonstrated that the proposed methods yielded promising results. [ABSTRACT FROM AUTHOR]

Close connections existing among sequence-dependent tasks should be emphasized while assembling products within automotive or electronic industries. This paper addresses the mixed-model assembly line balancing problem with sequence-dependent tasks with two objectives, the minimization of cycle time and workload variance. A hybrid genetic algorithm with novel logic strings was proposed to address the problem. First, both the sequence-dependent connections and precedence relations are integrated into the combined precedence graph so as to transform the original problem into the single-model assembly line balancing problem and to decrease the computational complexity. Second, three heuristic factors are hybridized into the process of initialization with the purpose of improving the quality of initial solution population. Third, considering sequence-dependent tasks, logic strings are designed to ensure the feasibility of chromosomes during two-point crossover and insertion mutation operations. Computational studies have demonstrated that the proposed algorithm can solve problems to near-optimality and even optimality with less computational effort. [ABSTRACT FROM AUTHOR]

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 function. 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. [ABSTRACT FROM AUTHOR]