A genetic algorithm for minimizing maximum lateness on parallel identical batch processing machines with dynamic job arrivals and incompatible job families

We consider the problem of minimizing maximum lateness on parallel identical batch processing machines with dynamic job arrivals. We propose a family of iterative improvement heuristics based on previous work by Potts [Analysis of a heuristic for one machine sequencing with release dates and delivery times. Operations Research 1980;28:1436–41] and Uzsoy [Scheduling batch processing machines with incompatible job families. International Journal for Production Research 1995;33(10):2685–708] and combine them with a genetic algorithm (GA) based on the random keys encoding of Bean [Genetic algorithms and random keys for sequencing and optimization. ORSA Journal on Computing 1994;6(2):154–60]. Extensive computational experiments show that one of the proposed GAs runs significantly faster than the other, providing a good tradeoff between solution time and quality. The combination of iterative heuristics with GAs consistently outperforms the iterative heuristics on their own.     

Nanoparticle‐Based Fluoroionophore for Analysis of Potassium Ion Dynamics in 3D Tissue Models and In Vivo

The imaging of real‐time fluxes of K⁺ ions in live cell with high dynamic range (5–150 × 10^?3m ) is of paramount importance for neuroscience and physiology of the gastrointestinal tract, kidney, and other tissues. In particular, the research on high‐performance deep‐red fluorescent nanoparticle‐based biosensors is highly anticipated. It is found that boron‐dipyrromethene (BODIPY)‐based K⁺‐sensitive fluoroionophore FI3 encapsulated in cationic polymer RL100 nanoparticles displays unusually strong efficiency in staining of broad spectrum of cell models, such as primary neurons and intestinal organoids. Using comparison of brightness, photostability, and fluorescence lifetime imaging microscopy, it is confirmed that FI3 nanoparticles display distinctively superior intracellular staining compared to the free dye. FI3 nanoparticles in real‐time live cell imaging are evaluated and it is found highly useful for monitoring intra‐ and extracellular K⁺ dynamics in cultured neurons. Proof‐of‐concept in vivo brain imaging confirms applicability of the biosensor for visualization of epileptic seizures. Collectively, these data make fluoroionophore FI3 a versatile cross‐platform fluorescent biosensor, broadly compatible with diverse experimental models, and crown‐ether‐based polymer nanoparticles can provide a new venue for the design of efficient fluorescent probes.     

Media Streams Scheduling for Synchronization in Distributed Multimedia Systems

In this paper, we consider the problem of multimedia synchronization based on scheduling the transmission of multimedia documents in a networked environment. Assuming channels with different bandwidth and delay characteristics are established between the multimedia server and the client, we formulate the scheduling problem to ensure interstream and intrastream synchronization as a parallel processor scheduling problem. Since the heterogeneous parallel processor scheduling problem is NP-hard, we propose two heuristic algorithms with time complexity ofO(n log n+nm), wherenis the number of data units to be scheduled andmthe number of channels available. We also develop an enumerative algorithm to obtain the exact solutions. Extensive computational simulations reveal that the heuristics consistently obtain near-optimal solutions. From the simulation results, we also identify special structures of multimedia documents along with characteristics of the available channels which affect the relative performance of the algorithms.     

Performance of decomposition procedures for job shop scheduling problems with bottleneck machines

Decomposition procedures for job shop scheduling problems, such as the shifting bottleneck (SB) procedure, have shown promising results for a variety of shop environments. However, they have primarily been tested using problems where all machines are identical in terms of processing time distribution. Many practical scheduling problems involve bottleneck machines which become the focus of scheduling efforts, as suggested by the theory of constraints. In this paper we examine the performance of several variants of SB, some of which can be interpreted as naive implementations of the TOC approach to scheduling. Our results show that both the solution time and quality of SB methods improve markedly when bottleneck workcentres are present. However, scheduling bottleneck machines optimally and using simple rules at other machines leads to poor performance unless the workload of the bottlenecks significantly exceeds that of the non-bottleneck machines.     

A REVIEW OF PRODUCTION PLANNING AND SCHEDULING MODELS IN THE SEMICONDUCTOR INDUSTRY PART II: SHOP-FLOOR CONTROL

In the first part of this review [62] we described the characteristics of semiconductor manufacturing environments and reviewed research on system performance evaluation and production planning. In this paper we focus on shop-floor control problems. We classify research to date by the solution techniques used, and discuss the relative advantages and disadvantages of the various approaches. We discuss the relationship between shop-floor control and production planning and suggest future research directions.     

Control of a batch-processing machine: A computational approach

Batch processing machines, where a number of jobs are processed simultaneously as a batch, occur frequently in semiconductor manufacturing environments, particularly at diffusion in wafer fabrication and at burn-in in final test. In this paper we consider a batch-processing machine subject to uncertain (Poisson) job arrivals. Two different cases are studied: (1) the processing times of batches are independent and identically distributed (IID), corresponding to a diffusion tube; and (2) the processing time of each batch is the maximum of the processing times of its constituent jobs, where the processing times of jobs are IID, modelling a burn-in oven. We develop computational procedures to minimize the expected long-run-average number of jobs in the system under a particular family of control policies. The control policies considered are threshold policies, where processing of a batch is initiated once a certain number of jobs have accumulated in the system. We present numerical examples of our methods and verify their accuracy using simulation.     

A neuro-fuzzy model for a new hybrid integrated Process Planning and Scheduling system

In customized mass production, isolation of Process Planning (PP) and Scheduling stages has a critical effect on the efficiency of production. In this study, to overcome this isolation problem, we propose an integrated system that does PP and Scheduling in parallel and responds to fluctuations in job floor on time. One common problem observed in integration models is the increase in computational time in conjunction with the increase of problem size. Therefore in this study, we use a hybrid heuristic model combining both Genetic Algorithm (GA) and Fuzzy Neural Network (FNN). To improve GA performance and increase the efficiency of searching, we use a clustered chromosome structure and test the performance of GA with respect to different scenarios. Data provided by GA is used in constructing an FNN model that instantly provides new schedules as new constraints emerge in the production environment. Introduction of fuzzy membership functions in Artificial Neural Network (ANN) model allows us to generate fuzzy rules for production environment.     

A survey of semiconductor supply chain models Part II: demand planning,inventory management,and capacity planning

Part I of this three-part series described semiconductor supply chains from the decision-making and functional perspectives, using this as a framework to review the industrial engineering and operations research literature on the problems arising in these supply chains. Part I then reviewed the literature on Strategic Network Design, supply chain coordination, sustainability and simulation-based decision support. This paper, Part II, reviews the areas of Demand Planning, Inventory Management and Capacity Planning in semiconductor supply chains. Part III concludes the series by discussing models to support Master Planning, Production Planning and Demand Fulfilment in this industry.     

Cycle-time improvements for photolithography process insemiconductor manufacturing

Cycle-time reduction is of great importance to semiconductor manufacturers. Photolithography, being one of the most repeated processes, is an area where substantial improvements can be made. We investigate the effects of various process control mechanisms for photolithography on the cycle-time at the process and at the overall fab via a simulation study. Test run policy at the photolithography station, test run frequency, duration of inspection, and machine dedication policy for the equipment are the factors we consider. Equipment down time due to preventive or breakdown maintenance and rework rates are also taken into account. Parallel testing, where test wafer is inspected while the lot is being processed, is the best policy in terms of cycle-time performance. Long inspection time and infrequent, long down times have the most adverse effects, but flexible machine assignment may reduce the impact of down times. Test run frequency is only significant for serial testing, where processing of the lot is not finished until the failed test wafer is stripped and reworked     

Media Streaming With Network Diversity

Today's packet networks including the Internet offer an intrinsic diversity for media distribution in terms of available network paths and servers or information sources. Novel communication infrastructures such as ad hoc or wireless mesh networks use network diversity to extend their reach at low cost. Diversity can bring interesting benefits in supporting resource greedy applications such as media streaming services, by aggregation of bandwidth and computing resources. Typically, overlay network architectures compensate for lack of quality-of-service guarantees in the network by introducing redundancy in the media delivery system through network diversity. They can support efficient multimedia services when routing, coding, and scheduling algorithms are able to adapt to both the media information and the dynamic network status. This paper presents an overview of the distributed streaming solutions that profit from network diversity in order to improve the quality of multimedia applications. We discuss the coding techniques used for adaptive and flexible media streaming with network diversity. We describe the problem of media streaming with path diversity and focus on routing, path computation, and packet scheduling problems in multipath networks. Then, the advantages of server or source peer diversity in collaborative streaming solutions are discussed. Lastly, we present an overview of wireless mesh networks and focus on the typical constraints imposed by these novel communication models on media streaming with network diversity.