A Scheduling Algorithm for Multi-Workshop Production Based on BOM and Process Route

For the scheduling problem of complex products in multi-workshop production, this paper studied the BOM (Bill of Materials) structure of complex products and the characteristics of the process route and developed the construction method of a multi-level process network diagram. Based on this, a comprehensive mathematical model for scheduling on multi-workshop production was proposed. An improved particle swarm algorithm (PSO) was proposed to solve the problem. By constructing the network subgraph, the invalid search path of the algorithm was avoided, and the efficiency of the algorithm was improved. In addition, for the scheduling problem with product time constraints, this paper presented a path search rescheduling strategy to ensure that the algorithm could obtain an effective search path. Finally, the model and algorithm were verified through a case study. This paper optimized the parameters of the algorithm by different tests and obtained the optimal range of the parameters. At the same time, through the analysis of the scheduling of complex products in a multi-workshop environment, the effectiveness and practicability of the above methods were verified.

Search Path Planning Algorithm Based on the Probability of Containment Model

The location of distress object in the maritime search area is difficult to determine, which has brought great difficulties to the search path planning. Aiming at this problem, a search path planning algorithm based on the probability of containment (POC) model for a distress object is proposed. This algorithm divides the area to be searched into several subareas by grid method and dynamically evaluates the POC of the distress object in each subarea using the Monte Carlo random particle method to build the POC model. On this basis, the POC is dynamically updated by employing the Bayes criterion within the constraint of the time window. Then, the sum of the POC of the object in the subareas is regarded as the weight of the search path. And the proposed algorithm dynamically executes the search path planning according to the maximum path weight. In comparison with the parallel line search path planning algorithm given in the “International Aeronautical and Maritime Search and Rescue Manual,” the simulation results show that the search path planning algorithm based on the POC model of the distress object can effectively improve the search efficiency and the probability of search success of the distress object.

Finding the Optimal Solution to the Problem of Conditional Optimization on the Graph of the set of Placements

The model of the problem of conditional optimization on the set of partial permutations is formulated. The linear form of the objective function is obtained by interpreting the elements of the set of partial permutations as points of the Euclidean space. A combinatorial polytope of allocations is considered for which there is a graph of the set of partial permutations An algorithm for solving this problem is proposed and its practical applicability is demonstrated. The proposed algorithm for solving the conditional optimization problem provides for the representation of the admissible of the Set of Partial Permutations in the form of a graph, which significantly reduces the search path for the optimal solution, as evidenced by the practical example considered.