A stochastic matching model on hypergraphs

Motivated by applications to a wide range of areas, including assemble-to-order systems, operations scheduling, healthcare systems, and the collaborative economy, we study a stochastic matching model on hypergraphs, extending the model of Mairesse and Moyal (J. Appl. Prob.53, 2016) to the case of hypergraphical (rather than graphical) matching structures. We address a discrete-event system under a random input of single items, simply using the system as an interface to be matched in groups of two or more. We primarily study the stability of this model, for various hypergraph geometries.

Maximum Utilization in Operations Scheduling for Multiple Machines and Batches in Additive Manufacturing

Scheduling and sequencing are forms of decision making that present a fundamental role in Additive Manufacturing (AM). This work studies the scheduling for a set of three-dimensional (3D) printers when the maximum utilization is used as an indicator. The aim is to establish a criterion that minimizes the use of available resources. A program has been done by using the software package Python and this has allowed studying the effect that the maximum utilization presents on operation scheduling. As evaluated a large number of pieces of various sizes, the analysis is found to be effective in yielding near-optimal solutions. The obtained outcomes have identified aspects of the production such as production planning and control as well as work organization.

Parallel Machine Production and Transportation Operations’ Scheduling with Tight Time Windows

This study addresses a parallel machine production and transportation operations’ scheduling problem with a tight time window associated with the transfer and delivery process. The orders located at the parallel machines need to be delivered to customers by train. Each order must be processed within a limited completion time in order for the product to be matched with the optimal trip to its destination within the delivery period. A mathematical analysis method is used to reveal the impact of tight time windows on the scheduling of production and transportation operations. The order transfer redundancy time and order transfer waiting time are employed to reflect the impact scheduling of production on the transfer process. The order delivery redundancy time and order delivery waiting time are used to describe delivery operations. The goal is to maximize the coordination level of order transfer and delivery, which are reflected in the order transfer time and the order delivery time, respectively. Additionally, a simulated annealing algorithm using the column generation technique was developed to solve this problem. The results show that the use of the system coordination model in this method obviously improves the number of successful transfers and deliveries.

Manufacturing 4.0 Operations Scheduling with AGV Battery Management Constraints

The industry 4.0 concepts are moving towards flexible and energy efficient factories. Major flexible production lines use battery-based automated guided vehicles (AGVs) to optimize their handling processes. However, optimal AGV battery management can significantly shorten lead times. In this paper, we address the scheduling problem in an AGV-based job-shop manufacturing facility. The considered schedule concerns three strands: jobs affecting machines, product transport tasks’ allocations and AGV fleet battery management. The proposed model supports outcomes expected from Industry 4.0 by increasing productivity through completion time minimization and optimizing energy by managing battery replenishment. Experimental tests were conducted on extended benchmark literature instances to evaluate the efficiency of the proposed approach.