Finite Scheduling Research Articles

Age of information for remote sensing with uncoordinated finite-horizon access

We analyze a remote sensing system in the Internet of things, where uncoordinated nodes send status updates to a common receiver to achieve information freshness, quantified through age of information. We consider a finite horizon scheduling over a random multiple access channel, where colliding messages are lost. We show that nodes must adopt a further randomization to deviate from identical schedules and escape collision deadlocks. Moreover, we discuss the impact of feedback availability if, due to, e.g., energy expenditure, it decreases the number of transmission opportunities.

Daratumumab Bortezomib and Dexamethasone in Transplant Ineligible Newly Diagnosed Elderly Myeloma Patients - a Trial By Asian Myeloma Network

Background: Transplant ineligible (TI) newly diagnosed Multiple Myeloma (NDMM) patients have inferior outcomes compared to that of a transplant population. This led to investigation of therapies with novel mechanisms of action to improve outcomes in this group. MAIA and ALCYONE studies have showed impressive outcomes in this group of patients. However, significant toxicities are a concern when delivering multiple anti-myeloma drugs concurrently in a continuous schedule in elderly patients. In this context, the efficacy and safety of Daratumumab, Bortezomib (finite) and dexamethasone in NDMM remains unknown. Aims: In this study, we investigated the combination of Daratumumab Bortezomib (in a finite schedule), and dexamethasone (DVd) followed by Daratumumab as maintenance in transplant ineligible TI NDMM patients from Asia (NCT03695744). Methods: This is a prospective, open-label, single-arm, phase 2 study of TI NDMM patients conducted by Asian Myeloma Network across three hospitals in Singapore. The primary end point was overall response rate. Secondary end points included progression free survival, overall survival, toxicity & safety, duration of response, minimal residual disease (MRD) and sustained MRD negativity. The study was approved by SingHealth Centralised IRB (CIRB No 2018/2730). Patients with confirmed diagnosis of MM, fulfilling inclusion / exclusion criteria were enrolled after signing informed consent. Patients received IV daratumumab 16mg/kg weekly in weeks 1-9, Q3 weekly from weeks 10 to 24 and Q4 weekly from week 25 onwards. Subcutaneous Bortezomib 1.3mg/m 2 and Dexamethasone 40mg (20mg for patients >75 years old) once weekly were administered for 9 months, followed by daratumumab maintenance until progression or toxicity. Response assessments were as per IMWG criteria and serial QOL data was also collected. Regular safety reviews were performed from recruitment of first patient by an independent committee. Here we report the protocol specified interim analysis of safety and efficacy end points. Results: From Oct 2019 till Sep 2021, we enrolled 27 patients. Median age was 74.3 years (range 70.5 to 79.2 years; 13/27 patients were >75years). 13 male and 14 were female patients. Ethnic distribution was 20 Chinese, 3 Malay, 3 Indian and 1 Others. ECOG performance status was 0 in 5(19%), 1 in 16(59%) and 2 in 6(22%) patients respectively. 11(41%) and 6(22%) patients belonged to Stage II and III ISS respectively. 14(52%) patients had CrCl <60ml/Min. 26(96%) patients experienced any grade adverse event with 17 experiencing a grade 3/4 event. Most common adverse events were infections, gastrointestinal disorders, peripheral neuropathy, and infusion related reactions. All grade and grade 3/4 AEs were relatively low, particularly haematological, given the absence of drugs known to cause significant myelotoxicity. Detailed AEs and SAEs are tabulated in Table 1. Three patients have died, of which one was due to a treatment related infection, while two others were unrelated (1 - suicide secondary to known mental illness, 1 - accidental fall & cervical spine injury). At data cut off (15 Oct 2022), 26 out of 27 patients had a response with 4(14.8%) sCR, 3 (11.1%) CR, 14 (51.9%) VGPR and 5 (18.5%) PR (1 missing assessment) giving an ORR of 96.3%. Median duration on Daratumumab was 16.3 mos and Bortezomib was 8 mos. 6 patients (22.2%) have experienced disease progression. With a median follow-up of 17.6 months, the 18-month progression free survival and overall survival were 65.4% & 89% respectively (median PFS and OS not estimable). Follow-up is on-going and we aim to report long-term survival, FISH/ cytogenetic & MRD results, toxicity and QOL data in future. Conclusion: DVd with Bortezomib in a finite schedule and Daratumumab maintenance achieved highly efficacious responses in elderly TI NDMM. Though this is a small study, toxicity rates here compare favorably to that noted in larger Phase 3 studies with quadruplets (Alcyone) and continuous triplet regimen as in the MAIA study. Whilst using novel agents like CD38 monoclonals upfront clearly improves responses and survival, minimizing toxicities without compromising efficacy by careful limitation of long-term concurrent exposure to multiple anti-myeloma drugs in an elderly population could help improve safety and quality of life. DVd could be an effective alternative in some elderly TI NDMM patients.

Finite State Machine-Based Load Scheduling Algorithm for Smart Home Energy Management

The problem of scheduling household appliances with the availability of renewable energy is the biggest challenge in the smart home energy management system. The components such as renewable energy resources, household appliances, utility grid, storage batteries are pooled into a nonlinear, time-varying, indefinite, and dynamic structure that is impossible to control and refine. For this, real-time pricing is applied in most nations to withstand the burden on the grid. This requires attention to utilize renewable energy effectively. In this paper, a load scheduling method to schedule the loads based on the availability of solar energy and customer preferences is presented. First, the availability of solar energy is forecasted ahead one day using Regression Analysis. Second, the finite state machine approach-based load scheduling algorithm is implemented and tested using MATLAB Simulink and Lab VIEW. LabVIEW-based GUI is developed to visualize the MATLAB schedule for loads. The problem is divided into several states with the availability of solar power, and if solar power is unavailable, grid power is utilized. The loads preferred by the consumers are scheduled in alignment with the production of solar power with the finite state machine scheduling algorithm. Also, the loads considered are able to consume instantaneous energy with the instantaneous production of energy, thereby reducing CO2 emission by not consuming power from the grid. Finally, the loads are scheduled accordingly, and it is concluded that coordination can be established between energy providers, and the system proposed can flatten out the load profile.

Performance analysis of XOR two‐way relay with finite buffers and instant scheduling

This study investigates the performance of practical wireless exclusive OR (XOR) two-way relay (TWR) system, in which finite buffer, lossy wireless channels and non-negligible signalling overhead are considered. Specifically, the authors develop a new analytical model to explicitly characterise the transmissions of both the end-nodes and the relay. The impact of scheduling on the throughput, queuing delay, power consumption and buffer overflow probability of XOR-TWR is evaluated. Validated by simulations, the model can precisely quantify the performance of XOR-TWR and adequately allocate the relay's buffer adapting to the wireless link qualities and signalling overhead.

Robust Task Scheduling for Multi-Operator Supervisory Control Missions

In future collaborative missions involving humans and unmanned aerial vehicles, especially those involving multiple human operators, the issue of resource allocation will be a crucial component to system success. Traditional deterministic strategies for task allocation and scheduling, such as those designed for job-shop applications, can often lead to poor performance in human-centered systems because these strategies fail to account for operator cognitive requirements or for the large amounts of uncertainty in human behavior. In light of this, a flexible framework that can potentially address both of these issues in finite horizon scheduling applications involving multiple operators is presented. Specifically, operator task load constraints are included as a part of a mixed integer program-based scheduling framework, which also incorporates robustness to uncertain processing times through the use of scenarios. The utility and modularity of this framework is then explored through the introduction of adaptive components that can further mitigate uncertainty and potentially boost performance. Finally, a heuristic, auction-based strategy is proposed for task allocation to reduce computation time to reasonable levels. Throughout the discussion, numerical examples are used to discuss the functionality of these algorithms, and various considerations for future practical implementation are discussed.

Organisational and technology management issues in a job shop environment

In a manufacturing planning and control (MPC) system, the shop floor control (SFC) back–end component provides detailed schedule information for each open order in the system. The absence of SFC is evidenced by excessive work–in–progress (WIP) inventories, resulting from excessive slack in scheduling operations. At one client company, the need for shop floor control was judged to be critical, yet the timing of the introduction of a fully integrated SFC was deemed inappropriate due to inadequacies in MPC. Instead, a custom, stand–along, finite capacity scheduler was developed. The package is intended to provide an interim capability only. The package runs on any PC compatible microcomputer, and utilises a user–friendly spreadsheet interface as a front–end. This paper deals with related issues in the design, implementation, and acceptance of a product which provides an interim shop floor control function in a job shop environment. It is seen that organisational issues can have a great impact on progress in the introduction and implementation of new systems, particularly when organisational structure, in this case the use of matrix management, encourages competition for control over the management of machine shop resources.

Bioisosteric Fluorine in the Clandestine Design of Synthetic Cannabinoids

Over the past decade, a plethora of indole-based synthetic cannabinoids (SCs) have emerged with their structures clearly inspired by scientific literature. Their structures continually evolve to elude detection by law enforcement and circumvent finite scheduling laws. The latest generation of SCs follow patent literature that encompasses a bioisosteric fluorine-for-hydrogen replacement commonly applied in medicinal chemistry. Unlike traditional pharmaceutical development, where rigorous preclinical evaluation is completed before human administration, these SCs are distributed for intended recreational consumption with little-to-no pharmacological data known. This highlight explores the evolution of SCs to this latest generation of fluorinated SCs where accumulating evidence indicates increased health concerns.

Implementing finite capacity production scheduling: lessons from a practical case

Many studies that have addressed the production scheduling problem refer to modelling and developing a solution. However, the academic literature presents a research–practice gap in this area with a lack of studies examining the implementation of production scheduling solutions in real contexts. This paper presents the lessons learned from the empirical findings of an action research on a successful implementation of computational simulators for finite capacity scheduling that were designed to help production schedulers in a large production plant of a global multinational motorcycle manufacturer. Although modelling the problem was important and required effort from the researchers, the main challenge revealed from the research was the model’s implementation on the shop floor. Issues regarding human, organisational and technological aspects were highlighted throughout the implementation process and proved essential for the solution to be effective.

Optimization of water distribution for open-channel irrigation networks

Water distribution for open-channel irrigation networks is more and more complex due to increasing constraints on water resources and changing demand patterns, whereas the performance of such systems is expected to increase. In this regard, an optimization approach is developed in order to schedule a fair scenario of water distribution among different users, where water demand is formulated in term of start time, duration and flow rate. This study investigates how to optimize the water distribution over a finite scheduling horizon while respecting the constraints linked to the system. The optimization approach forces the scheduled start time and the volume to be closer to the demanded ones, to minimize water losses and to reduce manpower. The constraints take into account the flow routing processes, the physical infrastructure, the available water resource, and the gate keeper timetable. The numerical resolution is done by using an optimization software IBM-Ilog Cplex. The method is then illustrated with the scheduling of off-take withdrawals for a typical traditional open-channel network: a lateral canal of the Gignac canal, in southern France.

A capacity available-to-promise model for drum-buffer-rope systems

The capacity available-to-promise (CATP) concept, which is designed to enhance the available-to-promise (ATP) feature in MRPII for changing production strategy from make-to-stock (MTS) to make-to-order (MTO), was developed recently. In contrast to an ATP, which is the future uncommitted inventory as projected by master production schedule, a CATP provides a detailed and time-phased diagram of unused production capacity. Hence, a CATP can allow marketing personnel to establish realistic order promise dates and concentrate on selling idle capacity in the future, and enable customers to select their preferred future capacity. This study proposes a CATP model for drum-buffer-rope (DBR) systems. The DBR scheduling system is one of finite capacity schedule systems and is currently being implemented by a growing number of manufacturing companies. This CATP model can help DBR users improve the due-date promising and exploitation of bottleneck. This CATP model can also be embedded in current commercial or private DBR scheduling systems so as to enhance their effectiveness.

Finite scheduling of collaborative design and manufacturing activity: a Petri net approach

PurposeThis paper aims to present an approach of utilizing Petri net (PN) to model and schedule collaborative design and manufacturing activities at a cyber manufacturing centre (CMC).Design/methodology/approachA conceptual PN model consisting of all activities at the CMC is drafted. This model is then simplified to generate a conflict free PN for scheduling analysis purposes. Based on this simplified PN, generalized scheduling algorithms were developed. The algorithms were used in spreadsheets to process and analyze the operation database before finally transforming it into a dynamic finite scheduling sequence in the form of Gantt chart.FindingsThe PN is found to be very useful in modelling and analysing the scheduling sequence for a CMC with collaborative activities resembling flow shop with shared resources.Originality/valueThe models and methods described in this paper are practical means of utilizing PN in managing the scheduling and manufacturing activities.

Lessons learned for building agile and flexible scheduling tool for turbulent environments in the extended enterprise

This paper presents results of a 2.5-year, multidisciplinary, university–industry collaborative effort investigating design of “Internet-based Scheduler for material Optimisation and agile ProducTion In MUlti-Site enterprises in agile manufacturing” (IS-OPTIMUS), a four nation collaborative project aimed at improvements in turbulent manufacturing environments. The focus of this paper is specifically on the content of the work carried out, along with the main benefits and results. Key to achieving the goals is following a complete project-life-cycle path from the initial stages where the industrial users requirements were identified and the system specification took place to the development and tuning of the final system. Design choices for software must strike a balance between the user flexibility required and the representing environment constraints, i.e. finite capacity scheduling, which takes production requirements from existing production planning systems, to schedule production resources like plant workers, critical tools and machines. The system consists of a material optimiser working closely with the finite capacity scheduler and a dynamic scheduler providing automatic reaction to real-time exceptions, thus deriving in solutions of higher performance.

Finite-horizon scheduling of radar dwells with online template construction

Timing constraints for radar tasks are usually specified in terms of the minimum and maximum temporal distance between successive radar dwells. We utilize the idea of feasible intervals for dealing with the temporal distance constraints. In order to increase the freedom that the scheduler can offer a high-level resource manager, we introduce a technique for nesting and interleaving dwells online while accounting for the energy constraint that radar systems need to satisfy. Further, in radar systems, the task set changes frequently and we advocate the use of finite horizon scheduling in order to avoid the pessimism inherent in schedulers that assume a task will execute forever. The combination of feasible intervals and online dwell packing allows modular schedule updates whereby portions of a schedule can be altered without affecting the entire schedule, hence reducing the complexity of the scheduler. Through extensive simulations we validate our claims of providing greater scheduling flexibility without compromising on performance when compared with earlier work based on templates constructed offline. We also evaluate the impact of two parameters in our scheduling approach: the template length (or the extent of dwell nesting and interleaving) and the length of the finite horizon.

Understanding and using the capabilities of finite scheduling

PurposePresents a microcomputer‐based finite scheduling approach to effective planning and execution of make‐to‐order production. Going beyond the traditional application of scheduling algorithms to prioritize jobs through work centers, the finite scheduling approach can be used to establish “smart” promise dates, manage the jobs through the work centers and enable supervisors to meet these due dates in the dynamic MTO environment.Design/methodology/approachUsing data from an operational jobshop and a simulation‐based finite scheduling algorithm linked to pre‐ and post‐processing capabilities developed in Access, this research provides specific examples of establishing smart due dates and managing resources to meet those dates. We provide some what‐ifs in order to more fully explore the benefits of a finite scheduling system.FindingsThrough use of actual jobshop data, the paper demonstrates that finite scheduling can be effectively performed on standard computing equipment. It also provides an understanding of finite scheduling and demonstrates that such a system can be of significant value in a MTO environment.Research limitations/implicationsFuture research could review/compare various ERP packages and their scheduling components to provide guidance on selection and implementation.Practical implicationsThe paper clearly indicates that managers, even of smaller companies, should be considering the use of finite scheduling.Originality/valueThe paper provides a new approach to finite scheduling using a combination of simulation and Microsoft Access on a personal computer. Additionally, it provides a very useful presentation for practitioners who want an understanding of finite scheduling and why they need to implement it.

Finite capacity scheduling—packed placement sequence schedule

This is one of a series of papers which describe the placement sequence approach to finite capacity scheduling of factories. A central aim of the placement sequence approach is to achieve well-packed and stable schedules, with multiple and alternative tools and machines, without the need for an iterative schedule improvement stage within the calculations. This means that calculations are bounded and the technique is suitable for large industrial applications. In this paper we treat schedule packing as the main goal and show how to build a ‘packed placement sequence schedule’. We use a two-stage process to choose the machines and placement sequence constraints. The first stage is a backward infinite capacity schedule and the second stage is a backward finite capacity schedule. While building the backward finite schedule we schedule using the order of event times from the infinite capacity schedule, and read the machine loading from the infinite capacity schedule so we can spread the load and push jobs away from the most heavily loaded machines in the finite capacity schedule. The final result is a well-packed, backward, finite capacity schedule. The paper explains the method, discusses the issues, and works through a detailed example of the calculations.

A Tight Flow Control for Job-Shop Fabrication Lines With Finite Buffers

We propose a work-in-process (WIP) estimation flow control method which serves as a countermeasure against the throughput degradation problem caused by the redundant blocking time of conventional flow control. This method is based on a scheduling technique of which the most important features are: 1) breaking down the entire schedule into individual lot schedules; 2) lot scheduling to reduce redundant blocking time; and 3) WIP estimation for contiguous finite buffer scheduling. The method, first, schedules operational lots at each equipment unit in a fabrication line by using our scheduling procedure for contiguous finite buffers to satisfy the limit capacity of the buffers. Next, the method estimates the future WIP at each equipment group based on predetermined schedules for performing operations. Finally, the method improves the operation timings by continuously supplying WIP estimation to the scheduling procedure. In an actual liquid crystal display (LCD) fabrication line simulation, we have confirmed that the proposed WIP estimation method is a promising one from the standpoint of the line throughput which we obtained.

Process planning and scheduling for mass customised shoe manufacturing

In the scenario of mass customization, production is a crucial phase of the whole product life cycle. Production planning and scheduling must therefore evolve and adopt new tools that help to obtain a deeper control of what has to be produced in order to satisfy efficiently customer’ needs. This is very important in the clothing and footwear (fashion) industry where customer's taste and choices change rapidly according to fashion dictates. In this paper an application in the footwear sector is presented and tested on a prototype of a new factory – an agile production unit – based on the concepts of agile and flexible production. The planning and scheduling module proposed is mainly focused on the short term in order to respond quickly to market needs and changes in a flexible manner. The module is composed of a finite capacity scheduler integrated with a new software based on the Analytical Hierarchy Process decision support system, which considers all the aspects related to order importance as complexity or urgency and assign each order a priority. This SW is able to take into account many intangible factors, as trademark, that are usually submitted to the subjective judge of the production manager (planner) and is completely configurable according to user’ needs. The result of the elaboration, that is the priority value, constitutes a fundamental input for the scheduler in addition to the due date of the order. The scheduler has a daily horizon because it is unnecessary to cover a long-time period if things can change every day following market requirements. The scheduler is configured to create all cycle operations for each single item even in order to manage orders composed of one pair or even one single shoe. This is a fundamental condition under a custom-made production focus. This also allows operation fine control and monitoring of the manufacturing process because the control system can identify exactly where each item at each time is in the system. Concluding, further developments are considered within a more integrated ad extended scenario applied to the automated production system in a new project where the full product life cycle including the customer, retailer shop and suppliers are taken into consideration.

Broadcast Disks with Polynomial Cost Functions

In broadcast disks systems, information is broadcasted in a shared medium. When a client needs an item from the disk, it waits until that item is broadcasted. Broadcast disks systems are particularly attractive in settings where the potential customers have a highly-asymmetric communication capabilities, i.e., receiving is significantly cheaper than transmitting. This is the case with satellite networks, mobile hosts in wireless networks, and Teletext system.The fundamental algorithmic problem for such systems is to determine the broadcast schedule based on the demand probability of items, and the cost incurred to the system by clients waiting. The goal is to minimize the mean access cost of a random client. Typically, it was assumed that the access cost is proportional to the waiting time. In this paper, we ask what are the best broadcast schedules for access costs which are arbitrary polynomials in the waiting time. These may serve as reasonable representations of reality in many cases, where the "patience" of a client is not necessarily proportional to its waiting time.We present an asymptotically optimal algorithm for a fractional model, where the bandwidth may be divided to allow for fractional concurrent broadcasting. This algorithm, besides being justified in its own right, also serves as a lower bound against which we test known discrete algorithms. We show that the Greedy algorithm has the best performance in most cases. Then we show that the performance of other algorithms deteriorate exponentially with the degree of the cost polynomial and approaches the fractional solution for sub-linear cost. Finally, we study the quality of approximating the greedy schedule by a finite schedule.

An integrated model for order release and due‐date demand management

In this paper, an integrated model for order release and due‐date management is developed to enhance manufacturers’ confidence in the due‐dates offered to customers. The proposed model utilised the backward finite scheduling order release control method and five different due‐date assignment rules. The proposed model is implemented using C++ computer programming language. Due‐date of each order is calculated by a due‐date assignment rule selected. Then the program tries to schedule the whole order with as lowest value as possible of tightness parameter (k). The output of the C++ program is production schedule of the whole order using backward finite scheduling order release method. Experiment results indicate that the modified number of operations due‐date rule_MNOP is superior with respect to the other due‐dates rules of the whole order.

Advanced Resource Planning

Advanced Resources Planning hits the bottom of what we know as aggregate planning. This approach differs from other approaches in that it explicitly recognizes the stochastic nature of manufacturing systems. Therefore, it is an ideal high-level tuning and planning tool which can be used in various planning environments like MRP, ERP, JIT, Load-Oriented Planning, Theory of Constraints, Finite Scheduling, POLCA systems, and perhaps many more. The main purpose is to set aggregate planning parameters right before diving into any other operational planning decision. In this sense, we opt to offer realistic lead time estimations, lot sizes, utilization levels, customer service levels and quoted delivery times. The underlying approach is a waiting line network, which is heavily adapted in order to make it useful for planning purposes. The main feature is that both input parameters and output parameters are considered as stochastic variables. In this way it allows us to model manufacturing environments in a more realistic and intuitive way, including all kinds of uncertainty and variability. As a consequence, the output of the planning effort is also a stochastic variable: it has an average, a variance and the entire lead time distribution. The latter makes it possible to obtain high customer service levels or to establish realistic delivery times, which can be met with a high probability. This mathematical approach as such is not suited for people operating a manufacturing system. We illustrate the approach with software, named i-CLIPS, and we review some implementations and their results.