Integrated Scheduling Algorithm Research Articles

Cloud-based smart agriculture framework: Optimizing load balancing efficiency via integrated scheduling algorithm

The rise of smart agriculture has revolutionized farming through advanced technology, boosting efficiency, productivity, and sustainability. This study introduces a Cloud-Based Smart Agriculture Framework that optimizes load-balancing efficiency through integrated hybrid scheduling algorithms. The four-layer framework aims to transform agricultural practices by combining IoT, Edge, Cloud, and Network layers. The research explores the crucial roles of IoT and Cloud Computing in Agriculture, emphasizing their contributions to data acquisition, analysis, and management. Integrating GA+ IRR in the IoT layer enhances load balancing and system optimization, improving resource management and optimizing data processing in agricultural IoT devices.

A Heuristic Integrated Scheduling Algorithm Based on Improved Dijkstra Algorithm

In the process of the integrated scheduling of multi-variety and small-batch complex products, the process structure and attribute characteristics are often ignored, which affects the overall scheduling effect. Aiming at solving this problem, a heuristic integrated scheduling algorithm (HIS-IDA) based on the improved Dijkstra algorithm is proposed. The algorithm takes the processing time of the process itself as the path value of the preceding and the following adjacent processes. Firstly, the improved Dijkstra algorithm prioritized the scheduling of the process sequence with long longitudinal paths and realized the “longitudinal optimization” of the integrated scheduling. Secondly, the layer priority strategy is used to shorten the interval time of process processing and realize the “horizontal optimization” of integrated scheduling. On the basis of “vertical and horizontal optimization”, the idle time of the equipment is further reduced by using the process priority strategy of the leaf node, and the “idle optimization” of the integrated scheduling is realized, so as to optimize the overall effect of the integrated scheduling. The effectiveness and superiority of the algorithm are proved using comparison analysis.

Symmetric Two-Workshop Heuristic Integrated Scheduling Algorithm Based on Process Tree Cyclic Decomposition

The existing research on the two-workshop integrated scheduling problem with symmetrical resources does not consider the complex product attribute structure and the objective situation of plant equipment resources. This results in the prolongation of the product makespan and the reduction of the utilization rate of the general equipment in the workshop. To solve the above problems, a two-workshop integrated scheduling algorithm based on process tree cyclic decomposition (STHIS-PTCD) was proposed. First, a workshop scheduling scheme based on the sub-tree cyclic decomposition strategy was proposed to improve the closeness of continuous processing further. Second, an operation allocation scheme based on the principle of workshop processing balance was presented. On the basis of ensuring the advantages of parallel processing, it also effectively reduces the idle time of equipment resources and then optimizes the overall effect of the integrated scheduling of both workshops. Through the comparison and analysis of all the existing resource-symmetric two-workshop integrated scheduling algorithms, the scheduling effect of the proposed algorithm is the best.

A signal-driven based flexible integrated scheduling algorithm with bidirectional coordination mechanism

A signal-driven based flexible integrated scheduling algorithm with bidirectional coordination mechanism

A novel integrated supply chain scheduling for cost optimization under flexible production and transportation

With the popularity of customized products, the interaction between the various stages of the supply chain has become more complex and closer. As for the scheduling of the twostage supply chain of production and transportation, current research treated production as a single operation, ignoring the impact of the flexible production process on inventory and transportation, and the overall optimization of the supply chain cannot be achieved. This paper focused on the problem of twostage flexible production and transportation supply chain integrated scheduling and proposed an improved geneticannealing algorithm to minimize the total cost of processing, inventory, transportation, and delivery. We proposed a novel multiple-chromosome encoding method to reflect the information of multiple decisions, including operation sequence, transportation batch, and customer delivery sequence, and a chromosomesrelated linkage crossover operator and a multipoint variation operator were designed on it. Two improvement strategies were used in the algorithm, including strategy of machine selection and strategy of batch optimization. The algorithm weighs the impact of decisions at each stage on total cost from an overall perspective to obtain the optimal combination solutions. Compared with the traditional two-stage scheduling algorithm, the proposed algorithm can save the inventory cost, transportation cost and the delivery cost in different scales of customers and orders. The results proved that the integrated scheduling algorithm can significantly save total cost and improve delivery service.

An Integrated Scheduling Algorithm for the Same Equipment Process Sequencing Based on the Root-Subtree Vertical and Horizontal Pre-Scheduling

Given the existing integrated scheduling algorithms, all processes are ordered and scheduled overall, and these algorithms ignore the influence of the vertical and horizontal characteristics of the product process tree on the product scheduling effect. This paper presents an integrated scheduling algorithm for the same equipment process sequencing based on the Root-Subtree horizontal and vertical pre-scheduling to solve the above problem. Firstly, the tree decomposition method is used to extract the root node to split the process tree into several Root-Subtrees, and the Root-Subtree priority is set from large to small through the optimal completion time of vertical and horizontal pre-scheduling. All Root-Subtree processes on the same equipment are sorted into the stack according to the equipment process pre-start time, and the stack-top processes are combined with the schedulable process set to schedule and dispatch the stack. The start processing time of each process is determined according to the dynamic start processing time strategy of the equipment process, to complete the fusion operation of the Root-Subtree processes under the constraints of the vertical process tree and the horizontal equipment. Then, the root node is retrieved to form a substantial scheduling scheme, which realizes scheduling optimization by mining the vertical and horizontal characteristics of the process tree. Verification by examples shows that, compared with the traditional integrated scheduling algorithms that sort the scheduling processes as an overall, the integrated scheduling algorithm in this paper is better. The proposed algorithm enhances the process scheduling compactness, reduces the length of the idle time of the processing equipment, and optimizes the production scheduling target, which is of universal significance to solve the integrated scheduling problem.

Multi-flexible integrated scheduling algorithm for multi-flexible integrated scheduling problem with setup times.

To address the multi-flexible integrated scheduling problem with setup times, a multi-flexible integrated scheduling algorithm is put forward. First, the operation optimization allocation strategy, based on the principle of the relatively long subsequent path, is proposed to assign the operations to idle machines. Second, the parallel optimization strategy is proposed to adjust the scheduling of the planned operations and machines to make the processing as parallel as possible and reduce the no-load machines. Then, the flexible operation determination strategy is combined with the above two strategies to determine the dynamic selection of the flexible operations as the planned operations. Finally, a potential operation preemptive strategy is proposed to judge whether the planned operations will be interrupted by other operations during their processing. The results show that the proposed algorithm can effectively solve the multi-flexible integrated scheduling with setup times, and it can also better solve the flexible integrated scheduling problem.

A Heuristic Integrated Scheduling Algorithm via Processing Characteristics of Various Machines

Complex products with a tree-like structure usually have an asymmetric structure. Therefore, in order to avoid the separation of equipment and operation correlation during the scheduling, the structural attributes of products and the use of equipment resources should be fully considered. However, this feature is ignored in the current research works on the scheduling of multi-variety and small batch products. This leads to increased idle time for equipment and an extended makespan for products. To avoid this situation, a heuristic integrated scheduling algorithm via processing characteristics of various machines (HIS-PCVM) is proposed. In the integrated scheduling, the algorithm first divides the equipment into two categories: the special equipment and the general equipment according to the resources of the production scheduling system. Then, different scheduling methods are designed according to the equipment categories. The makespan of the product is further optimized through various combination methods. Moreover, the constraint audit strategy to guarantee the constraint relationship between the operations is optimized. The earliest scheduling time strategy is proposed to improve the parallelism and serial tightness of the operations. These strategies reduce the idle time of equipment effectively. Experimental results show that the proposed algorithm has a better application effect in reducing the makespan of complex products, both with asymmetric structures and symmetric structures. This also shows that the algorithm is effective in improving the utilization rate of equipment.

An Integrated Scheduling Algorithm Based on a Process End Time-Driven and Long-Time Scheduling Strategy

The integrated scheduling problem is a classical combinatorial optimization problem. The existing integrated scheduling algorithms generally adopt the short-time scheduling strategy that does not fully consider the impact of the degree of process parallelism on scheduling results. In order to further optimize the total processing time of a product and the utilization rate of a device, an integrated scheduling algorithm based on a process end time-driven and the long-time scheduling strategy is proposed. The proposed integrated scheduling algorithm sets up a separate candidate process queue for each device and determines the scheduling order for each scheduling queue on the premise of satisfying the constraint conditions of the process tree. Driven by the process end time, the algorithm finds schedulable processes for each device. If the schedulable process is unique, it is scheduled. Otherwise, if the schedulable process is not unique, the process with long-path and long-time is scheduled. In particular, the scheduling strategies of the scheduling queues of different devices are symmetric, and the constraint relationships between the processes in different queues are asymmetric. The case analysis results show that the proposed integrated scheduling algorithm is better than some existing algorithms in terms of the total processing time of a product and the average utilization rate of devices. Therefore, the proposed algorithm provides a new idea for processing the scheduling of a single complex product.

Integrated Scheduling Algorithm of Two Workshops Based on Process End Time Driven and Processing Area Priority

In order to effectively allocate processes of Aa single complex product to two workshops with the same equipment, an integrated scheduling algorithm of two workshops based on process end time driven and processing area priority is proposed. To optimize the total processing time, a process scheduling strategy based on process end time driven is proposed. By scheduling multiple devices at the same time, the parallelism of process execution is improved, in order to reduce the total processing time and improve the utilization rate of equipment. In order to optimize the process migration times between two workshops, a workshop assignment strategy based on process processing area priority is proposed, which comprehensively considers the influence of the immediate preceding process, neighbor process and friend process of the schedulable process on workshop assignment and makes the process in the same processing area be processed in the same workshop as much as possible, so as to reduce the process migration times. The example analysis shows that the proposed algorithm is superior to the existing two workshops integrated scheduling algorithms in terms of reducing the total processing time, reducing the process migration times, and improving the utilization rate of equipment.

A Reverse Order Hierarchical Integrated Scheduling Algorithm Considering Dynamic Time Urgency Degree of the Process Sequences

Aiming at the general integrated scheduling problem of tree-structured complex single-product machining and assembling, a reverse order hierarchical integrated scheduling algorithm (ROHISA) is proposed by considering the dynamic time urgency degree (TUD) of process sequences (PSs). The strategy of process sorting is put forward, and the TUD of PS is defined. The process tree is reversed using leaf alignment, and according to the order from leaf to root, the scheduling order of leaf nodes in the same layer is determined layer by layer according to the TUD values of the PSs to which the leaf nodes belong. In turn, the sorted leaf nodes in each layer are stored in a corresponding layered array (LA). Finally, the elements in each LA are reversed, and the LAs’ arranging order is reversed. A reverse order hierarchical scheduling strategy is proposed. Starting from the root node, every LA is taken as a unit to conduct trial scheduling each time. Under the condition of meeting the craft constraints, a set of quasi-scheduling schemes of same-layer processes (QSSSLP) is obtained, and the one with the minimum end time is selected from it as the scheduling scheme of the same layer processes (SSSLP). If it is not unique, the QSSSLP that machines all the same layer processes (SLP) as early as possible is selected. The research shows that the ROHISA optimizes the integrated scheduling results of single-product manufacturing enterprises and improves its production efficiency.

A Flexible Integrated Scheduling Algorithm for Dynamic Determination Processing Equipment Considering the Root-Subtree Vertical and Horizontal Pre-Scheduling

Aiming at the existing flexible integrated scheduling algorithms that use unified rules to solve the conflicts between processes and equipment, and ignore the vertical and horizontal characteristics of the process relative positions in the process tree, a flexible integrated scheduling algorithm for dynamic determination processing equipment considering the Root-Subtree vertical and horizontal pre-scheduling (FISA-DEVH) is proposed. The process sorting strategy of the Root-Subtree vertical and horizontal pre-scheduling is proposed to sort the Root-Subtree processes of the same planned processing equipment in groups and load the Root-Subtree processes into the corresponding equipment queues, so as to fully explore the vertical and horizontal characteristics of the process. In order to give full play to the characteristics of the flexible equipment and realize the effective parallel processing between the processes, the flexible equipment optimal scheduling strategy of dynamically determining process is proposed to determine the final processing equipment of the process at each equipment driving moment and complete the production scheduling process from the Root-Subtree static pre-scheduling to dynamic fusion; The strategy uses the scheduling relationship between the unplanned processes and unplanned equipment to reduce the search scope of the combination scheme and improve the efficiency of the algorithm. The example tests show that FISA-DEVH has a better scheduling effect than the flexible integrated scheduling algorithm that processes the process tree with unified rules, and has universal significance for solving the flexible integrated scheduling problem.

An integrated scheduling algorithm for multi-device-processes with the strategy of exchanging adjacent parallel processes of the same device

At present, Multi-Devices-Process Integrated Scheduling Algorithm with Time-Selective Strategy for Process Sequence (MISATPS) is an advanced algorithm in the field of integrated scheduling with multi-devices-process problems. This algorithm ignores the influence of the pre-process on the post-process when solving the multi-devices-process integrated scheduling problem, which leads to the problem of poor closeness between serial processes and poor parallelism between parallel processes. This paper points out that there is no restriction of scheduling sequence between parallel processes on the same processing device. It can be scheduled flexibly of the sequence between parallel processes of the same device. Therefore, based on the scheduling scheme of MISATPS, the algorithm is improved by applying the interchange strategy and the interchange adjustment strategy of multi-device adjacent parallel process. In this way, the influence of the pre-process on the post-process is avoided, the compactness of the serial process and the parallelism of the parallel process are improved, and the scheduling result is optimized.

An Improved Integrated Scheduling Algorithm with Process Sequence Time-Selective Strategy

The integrated scheduling algorithm of process sequence time-selective strategy (ISAOPSTSS) is an advanced algorithm in the field of integrated scheduling. The proposed algorithm points out the shortcomings of the process sequence time-selective strategy. Generally, there are too many “trial scheduling” times. The authors propose that there is no need to make “trial scheduling” at every “quasi-scheduling time point.” In fact, the process scheduling scheme can be obtained by trial scheduling on some “quasi-scheduling time points.” The scheduling result is the same as that of the sequence timing strategy. The proposed algorithm reduces the runtime of scheduling algorithm and improves the performance of the algorithm without reducing the optimization effect.

Flexible integrated scheduling algorithm based on remaining work probability selection coding

AbstractAiming at the integrated scheduling problem of tree‐structured products with flexible machine selection, this article proposes a flexible integrated scheduling algorithm based on remaining work probability selection coding. The algorithm is based on the framework of a genetic algorithm. First, in order to ensure the diversity and goodness of the initial population, an encoding method based on remaining work probability selection is proposed. Second, two new different crossover and mutation methods are designed based on operation and position respectively, which ensure the legitimacy of the generated offspring individuals. Then, in order to enhance the searchability of the algorithm for an optimal solution of the problem, a local search strategy based on the machine is proposed. Finally, a simple and effective decoding method based on the idle period is given. The algorithm is tested by the existing instance and randomly generated instances. The experimental results show that the proposed algorithm's solving speed and solution quality outperform other comparison algorithms.

A multi-shop integrated scheduling algorithm with fixed output constraint

The customized products such as electromechanical prototype products are a type of product with research and trial manufacturing characteristics. The BOM structures and processing parameters of the products vary greatly, making it difficult for a single shop to meet such a wide range of processing parameters. For the dynamic and fuzzy manufacturing characteristics of the products, not only the coordinated transport time of multiple shops but also the fact that the product has a designated output shop should be considered. In order to solve such Multi-shop Integrated Scheduling Problem with Fixed Output Constraint (MISP-FOC), a constraint programming model is developed to minimize the total tardiness, and then a Multi-shop Integrated Scheduling Algorithm (MISA) based on EGA (Enhanced Genetic Algorithm) and B&B (Branch and Bound) is proposed. MISA is a hybrid optimization method and consists of four parts. Firstly, to deal with the dynamic and fuzzy manufacturing characteristics, the dynamic production process is transformed into a series of time-continuous static scheduling problem according to the proposed dynamic rescheduling mechanism. Secondly, the pre-scheduling scheme is generated by the EGA at each event moment. Thirdly, the jobs in the pre-scheduling scheme are divided into three parts, namely, dispatched jobs, jobs to be dispatched, and jobs available for rescheduling, and at last, the B&B method is used to optimize the jobs available for rescheduling by utilizing the period when the dispatched jobs are in execution. Google OR-Tools is used to verify the proposed constraint programming model, and the experiment results show that the proposed algorithm is effective and feasible.

Multiple-Devices-Process Integrated Scheduling Algorithm with Time-Selective Strategy for Process Sequence

This paper is in view of the current algorithm to solve Multiple-Devices-Process integrated scheduling problems without considering parallel process between the parallel processing. Meanwhile, the influence of the first processing procedure on the second processing procedure is ignored, resulting in poor tightness between serial processes and poor parallelism between parallel processes, ultimately affecting the product scheduling results. We proposed Multiple-Devices-Process integrated scheduling algorithm with time-selective for process sequence. The proposed Multiple-Devices-Process sequencing strategy determines the process of scheduling order and improves the tightness between serial process. This paper presents a method to determine the quasischeduling time point of the multiequipment process, the time-selective strategy of Multiple-Devices-Process, and the time-selective adjustment strategy of Multiple-Devices-Process so that the first and the second processing processes cooperate with each other, and the purpose of improving the tightness of the serial process and the parallelism of the parallel processes is achieved, so as to shorten the product processing time.

A hybrid algorithm for integrated scheduling problem of complex products with tree structure

Due to the poor design of encoding methods or evolutionary operators in previous genetic-algorithm-based integrated scheduling algorithms, this paper proposes an integrated scheduling algorithm based on a hybrid genetic algorithm and tabu search. Firstly, an encoding method based on a dynamic schedulable operation set is proposed. This method cannot only reflect the priority constraints among operations, but also avoid the problems of imposing constraints and missing solution space in previous division encoding method. Secondly, a decoding method based on machine idle time driving is presented to handle the scheduling order of operations on different machines. Then, two different discrete crossover and mutation operators are designed to ensure the legitimacy of the processing sequence of the same machine. Finally, a local search strategy based on tabu search is shown to enhance the search capability for superior solutions. The algorithm is tested by the randomly generated instances, and the experimental results indicate that the proposed algorithm is effective and can achieve satisfactory performance.

Large-Scale Intelligent Taxicab Scheduling: A Distributed and Future-Aware Approach

Intelligent taxicab scheduling systems on smartphones continue to gain popularity as they offer prominent conveniences for urban travelling as well as increase potential profits for taxicab drivers, hence inject prosperity and vitality into intelligent transportation and urban business. Existing scheduling approaches usually fall into biases and myopia due to their single target perspective of satisfying the immediate order acceptance, or maximizing the global business success rates.However, the highly complex spatiotemporal dependencies among multiple factors and the efficiency bottleneck of massive order flows make the taxicab scheduling issue still challenging. To this end, in our paper, we propose an integrated scheduling algorithm with both future-aware and context-aware mechanisms. In particular, we first present a generalized graph-based framework which aims to capture traffic dependencies, providing precise and quantified supply-demand prediction in taxicab scheduling. Then, we develop a measurement of regional supply-demand context to perform cooperative and distributed scheduling. To tackle the efficiency bottleneck in massive order flow scenario, we correspondingly design a model to learn business patterns with considering benefits from both drivers and passengers, and further promote service delivery rates via a novel bi-incentive strategy. Extensive numerical studies illustrate the remarkable significance of our method, in terms of both service delivery rates and global driver revenues. The promising results and brand-new perspectives enable our algorithm to be a paradigm in general spatiotemporal scheduling tasks.

Multi-batch integrated scheduling algorithm based on time-selective

Based on the problem that the integrated scheduling algorithm cannot fully consider the impact of the scheduling process on the subsequent process so that the scheduling results are impacted, this paper presents a multi-batch integrated scheduling algorithm based on time-selective. This algorithm proposes a process sequence sequencing strategy,it divides the whole structure of the process tree into several process sequences and determines the scheduling order according to the path length. The multi-batch time-selective scheduling strategy generates several process combination plans. It presents the process combination selection strategy chooses the combination plan most close to scheduling targets among the different combination plans. The analysis and example show that this algorithm is better in multi-batch integrated scheduling.