The Batch Machine Scheduling of Continuous Caster with Flexible Jobs to Minimize Setup Costs

Remanufacturing has become a Frontier technology in sustainable manufacturing and enables end-of-life products to be restored to their new conditions. Although remanufacturing scheduling has been widely investigated, the relationship between remanufacturers and customers is rarely examined. Therefore, a new game-relationship-based remanufacturing scheduling model with sequence-dependent setup times is proposed herein. In the model, the relationship between the remanufacturer and customers is constructed as a non-cooperative game, and the interval due dates are set based on the uncertain product quality to achieve effective remanufacturing and improve customer satisfaction. Multiple remanufacturing lines differentiated based on the quality grade of products are integrated into the proposed model. In addition, sequence-dependent setup times are considered in the model, which depend on the similarity between two adjacent tasks processed on a reprocessing unit. An improved discrete particle swarm optimization algorithm is proposed to obtain Nash equilibrium solutions via an efficient global search structure and a local search strategy. The algorithm is embedded with the Nash equilibrium solution evaluation method and integrated with multiple genetic operators to update the particles. The performance of the proposed algorithm in solving the proposed model is verified via a comparison with three baseline algorithms for managing different problem instances.

Section: Relevant Literaturementioning

confidence: 99%

Game-relationship-based remanufacturing scheduling model with sequence-dependent setup times using improved discrete particle swarm optimization algorithm

Zhang

et al. 2022

“…Because the parameters of due date, upper bound, portion of agent 1, and learning effect vary, there are many local minimums in the solution space. Consequently, general-purpose evolutionary algorithms and local searches will be easily trapped in the local minimums (Ji et al, 2013; Yu and Huang, 2011). Therefore, particular scheduling algorithms are called for.…”

Section: Problem Descriptionmentioning

confidence: 99%

Algorithms for single-machine scheduling to minimize the total tardiness with learning effects and two competing agents

Lee

Wang

2014

Scheduling with learning effects or scheduling with two competing agents has been widely studied in recent years. However, they are seldom discussed at the same time. In this article, we consider a single-machine scheduling problem with learning effects where the objective is to minimize the total tardiness of jobs from one agent, given that the maximum tardiness of jobs from the other agent cannot exceed an upper bound. We provide a branch-and-bound algorithm to search for the optimal solution and a genetic algorithm equipped with a local search to obtain near-optimal solutions. In addition, we conduct some computational experiments to investigate the solution quality and execution speed of both algorithms.

“…For the analysis of an automated manufacturing system, simulation technology has been considered as an essential tool (Iwata et al, 1995). Simulation is useful for calculating utilization statistics, finding bottlenecks, pointing out scheduling errors, and even for creating manufacturing schedules (Yu and Huang, 2011).…”

Section: Introductionmentioning

confidence: 99%

A concurrent design methodology of a production system for virtual commissioning

Ahn

Park

2013

In this article, a concurrent design procedure of a production system is presented, which supports the virtual commissioning between a real controller and a virtual plant consisting of virtual devices. To achieve the concurrency, we split a virtual device model into two parts, a physical device model (a geometric model with kinematics for the motion programming of tasks) and a logical device model (a behavioral model to interact with a real controller). The whole design procedure consists of four major steps: (1) process design, (2) physical device modeling, (3) logical device modeling, and (4) system control modeling. First, the process design step identifies effective manufacturing processes and produces the sequence of operations. Once the sequence of operations is obtained at Step 1, then the other three steps can be performed concurrently without interfering each other. All the three concurrent steps start from the sequence of operations, and a detailed procedure for each of the step has been developed. The concurrent attribute of the proposed design procedure significantly contributes to the saving of the delays in time to market. The proposed design procedure has been implemented and tested for various examples.