Linear Deterioration Research Articles

Single-machine group scheduling with general linear deterioration and truncated learning effects

Single-machine group scheduling with general linear deterioration and truncated learning effects

A comprehensive analysis of linear and non-linear deterioration rates in dual-warehouse inventory systems

This study presents an inventory system where items have an initial linear deterioration rate that transitions to a non-linear pattern, addressing a critical aspect of contemporary supply chain management. Our research introduces a dual warehouse inventory model comprising a rented facility and utilizing an owned warehouse. This unique approach is geared towards products experiencing a shift in deterioration rates, starting linearly and progressing non-linearly. The model operates under a constant demand rate, allowing for partial backlogging during shortages. Key to our analysis are distinct holding costs assigned to each warehouse, reflecting real-world scenarios. We derive conditions that minimize the total cost, supporting these with numerical examples spanning various parameter settings. A comprehensive sensitivity analysis evaluates the influence of each parameter’s alteration, keeping others constant. This analysis illuminates the model’s robustness and adaptability to different operational contexts. The findings offer significant managerial implications, providing valuable insights for effectively managing inventory in scenarios where product deterioration rates change over time. Our approach distinguishes itself by integrating linear and non-linear deterioration patterns within a dual warehouse system, a novel contribution to inventory management literature. The practical relevance of our model is underlined by its applicability in diverse supply chain environments, making it an essential tool for contemporary inventory management strategies.

A Customized IMOEA/D for Bi-Objective Single-Machine Scheduling with Adaptive Preventive Maintenance

The prolonged operation of machines in the production process can lead to continuous deterioration or even failure, and the necessary maintenance measures can alleviate the above negative effects. For this reason, this study investigates a joint optimization problem of single-machine production and preventive maintenance (PM) considering linear deterioration effects. The objective is to obtain an integrated sequence of degrading jobs and PM activities in order to simultaneously minimize the makespan and the total cost. Based on the problem characteristics, an adaptive PM strategy is first designed. To efficiently solve the problem, an improved multi-objective evolutionary algorithm based on decomposition (IMOEA/D) is tailored, where the biased-distribution weight vector is proposed to enhance the search capability at both ends of the Pareto front. Five instances are used to evaluate the performance of the customized IMOEA/D and two classical multi-objective evolutionary algorithms. Numerical studies show that the IMOEA/D can substantially improve the hypervolume metric, the maximum spread metric, and the distributivity of the Pareto front at a slight sacrifice of the spacing metric.

Scheduling jobs with general linear deterioration to minimize total weighted number of late jobs

Scheduling jobs with general linear deterioration to minimize total weighted number of late jobs

Evolution Analysis of Asphalt Pavement Performance in Its Life Cycle: Case Study in Qinghai–Tibet Highway

Owing to the combination of bitumen aging, traffic loading, and environmental factors, the performance of asphalt will gradually deteriorate with time. However, characterizing the deterioration is still challenging. Aiming to reveal how the performance of asphalt pavement deteriorates with time, the AASHTO design equation was applied to investigate the evolution trend of pavement performance by adopting a reliability method in terms of freeze–thaw cycles. It was found that the combination of the rate of evolution and curvature could identify the abrupt change points and significant variation stages. Risk analysis was introduced to provide a novel method to evaluate the pavement performance evolution by identifying the change of the hazard rate and the cumulative hazard rate. It was found that the evolution curve of asphalt pavement strength reliability could be divided linearly during its life cycle, which can be extended to any n-stage linear deterioration model according to the actual situation. Moreover, reliability levels for pavement strength were also proposed in this research according to the integrated pavement travel and structure performance.

Credibility based chance constrained programming for parallel machine scheduling under linear deterioration and learning effects with considering setup times dependent on past sequences

The industry has expressed significant concern regarding the issue of parallel machines and the influence of learning and deterioration. This research investigates non-identical parallel machine scheduling, taking into account the simultaneous consideration of learning effects, deterioration, and past-sequence-dependent setup times. Due to the existence of uncertain parameters in real-world scenarios, the processing times and due dates are assumed to be triangular fuzzy numbers. A fuzzy nonlinear mathematical model with two objective functions is presented and solved using the fuzzy Chance Constraint Programming approach. The two objectives are the summation of earliness and tardiness, as well as makespan. To achieve an efficient near-optimal Pareto front for the problem, a hybrid NSGA-II and VNS multi-objective meta-heuristic is proposed and the results are discussed. Finally, the augmented ε-constraint method is utilized to address issues with small dimensions. The computational analysis demonstrates the effectiveness of this proposed algorithm in tackling problems, especially those with substantial dimensions.

Single‐Machine Group Scheduling Problems with General Deterioration and Linear Learning Effects

In this paper, we introduce a group scheduling model with deterioration and a general linear learning effect. The group setup time is a linear deterioration function of its starting time. The general learning effect is time‐dependent and position‐dependent. The objectives are to minimize the makespan, total completion time, and total weighted completion time, respectively. We show the problems remain solvable in polynomial time under the proposed model.

Green scheduling of packaging in the global logistics distribution centre with a dominant job and deterioration effects

ABSTRACT This paper studies an energy-efficient parallel packaging machine scheduling problem in the global logistics distribution centre considering a dominant job and the linear deterioration effect. The objective is to minimise total energy costs. First, we discuss the structural properties of the single-machine scheduling problem without a dominant job. Then, for the single-machine scheduling problem with a dominant job, we divide the problem into three situations depending on the time window requirement of the special customer. Based on the structural properties, two heuristic algorithms are designed to solve the single machine scheduling problem with or without a dominant job. For the parallel-machine scheduling problem, we develop four neighbourhood structures and propose a variable neighbourhood search (VNS) algorithm to find the near-optimal solution in a reasonable time. Finally, computational experiments are conducted, with the results validating the effectiveness of the designed neighbourhood structures and the VNS algorithm.

Trajectory Pattern of Cognitive Decline in Cerebral Autosomal Dominant Arteriopathy With Subcortical Infarcts and Leukoencephalopathy.

Background and ObjectivesThe course and pattern of cognitive decline in ischemic cerebral small vessel disease remain poorly characterized. We analyzed the trajectory pattern of cognitive decline from age 25 to 75 years in cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL).MethodsWe applied latent process mixed models to data obtained from patients with CADASIL who were repeatedly scored during their follow-up using 16 selected clinical scales or cognitive tests.ResultsThe modeled evolutions of these scores obtained from 1,243 observations in 265 patients recruited at the French National Referral Centre (50.1 years on average and 45.3% men) showed wide and heterogeneous variations in amplitude along the age-related progression of the disease. Although the Backward Digit Span remained essentially stable, a linear deterioration of scores obtained using the Symbol Digit Numbers or Number of Errors of Trail Making Test B was detected from 25 to 75 years. By contrast, the largest score changes were observed at midlife using the Digit Cancellation Task. All other tests related to executive functions, memory performances, or global cognitive efficiency showed a rate of change accelerating especially at the advanced stage of the disease. Male gender and the presence of gait disorders or of some disability at baseline were found to predict earlier or large changes of 4 scores (Index of Sensitivity to Cueing, Delayed Total Recall, Initiation/Perseveration, and Barthel Index) in a subgroup of individuals distinct from the rest of the sample.DiscussionCognitive alterations develop heterogeneously during the progression of CADASIL and vary largely according to the stage of the disease. These results suggest that not only the target population and study duration but also the stage of disease progression should be considered in preparing future clinical trials aimed at reducing cognitive decline in any such condition.

Minimizing total completion time with linear deterioration: A new lower bound

We study scheduling problems in which the job processing times are linearly deteriorating. Each job has a constant (job-independent) basic processing time and a job-dependent deterioration rate. The objective function is minimum total completion time. The machine settings considered are: single machine and parallel identical machines. The complexity status of these problems has been an open question for the last three decades. We introduce a new lower bound on the optimal total completion time, which is shown numerically (through a comparison to the results obtained by a simple heuristic) to be extremely accurate for both problems.

Wearable inertial sensors are highly sensitive in the detection of gait disturbances and fatigue at early stages of multiple sclerosis

BackgroundThe aim of the current study was to examine multiple gait parameters obtained by wearable inertial sensors and their sensitivity to clinical status in early multiple sclerosis (MS). Further, a potential correlation between gait parameters and subjective fatigue was explored.MethodsAutomated gait analyses were carried out on 88 MS patients and 31 healthy participants. To measure gait parameters (i.e. walking speed, stride length, stride duration, duration of stance and swing phase, minimal toe-to-floor distance), wearable inertial sensors were utilized throughout a 6-min 25-ft walk. Additionally, self-reported subjective fatigue was assessed.ResultsMean gait parameters consistently revealed significant differences between healthy participants and MS patients from as early as an Expanded Disability Status Scale (EDSS) value of 1.5 onwards. Further, MS patients showed a significant linear trend in all parameters, reflecting continuously deteriorating gait performance throughout the test. This linear deterioration trend showed significant correlations with fatigue.ConclusionsWearable inertial sensors are highly sensitive in the detection of gait disturbances, even in early MS, where global scales such as the EDSS do not provide any clinical information about deviations in gait behavior. Moreover, these measures provide a linear trend parameter of gait deterioration that may serve as a surrogate marker of fatigue. In sum, these results suggest that classic timed walking tests in routine clinical practice should be replaced by readily and automatically applicable gait assessments, as provided by inertial sensors.

Optimal sequence for single server scheduling incorporating a rate-modifying activity under job-dependent linear deterioration

This study considers single processor scheduling problems incorporating a rate-modifying activity (RMA) as well as processing time deterioration rates. The RMA fully restores the processing speed of a processor. As discussed in recent literature, the optimal position of an RMA for a single processor scheduling problem with the objective of makespan minimization, 1|p[j]A=α[j]S[j],rm|Cmax, where the processing time of a job (p[j]A:[j]denotesthejthposition)is determined by its start time (S[j])and position-dependent rate (α[j]), can be found easily. This study considers six variants of the problem: (P1) 1|p[j]A=p¯+α[j]S[j],rm|Cmax, (P1+)1|p[j]A=p¯+α[j]S[j],drm|Cmax, (P2) 1|p[i,j]A=pj+α[i]Sj,rm|Cmax, (P2+)1|p[i,j]A=pj+α[i]Sj,drm|Cmax, (P3) 1|pjA=αjSj,rm|Cmax, and (P3+)1|pjA=αjSj,drm|Cmax, where p¯ is the common basic processing time, pjis the basic processing time for job j, [i,j] is the job j scheduled at the ith position, and drm is the deteriorating RMA. We show that (P1) and (P1+), where the common basic processing time is considered, can be converted into the problem 1|p[j]A=α[j]S[j],rm|Cmax, so that the optimal position of the RMA can be found easily. In the other variants, the optimal sequences of jobs and positions of the RMA must be determined. In (P2) and (P2+), the basic processing time for each job (pj)is considered, whereas, in (P3) and (P3+), the deterioration rate depends not on the position of the job (α[j]) but on the job itself (αj). We show that the optimal schedules for (P2), (P2+) and (P3), (P3+) can be found by solving the assignment problems and the knapsack problems, respectively.

A Genetic Algorithm Approach to Parallel Machine Scheduling Problems Under Effects of Position-Dependent Learning and Linear Deterioration

This paper investigates parallel machine scheduling problems where the objectives are to minimize total completion times under effects of learning and deterioration. The investigated problem is in NP-hard class and solution time for finding optimal solution is extremely high. The authors suggested a genetic algorithm, a well-known and strong metaheuristic algorithm, for the problem and we generated some test problems with learning and deterioration effects. The proposed genetic algorithm is compared with another existing metaheuristic for the problem. Experimental results show that the proposed genetic algorithm yield good solutions in very short execution times and outperforms the existing metaheuristic for the problem.

Infliximab De-escalation in Patients With Crohn's Disease in Clinical Remission Is Safe and Well-tolerated.

Infliximab—a chimeric monoclonal antibody that targets antitumor necrosis factor (TNF) alpha—is an effective biological agent to treat inflammatory bowel disease (IBD).1 Infliximab has demonstrated long-term therapeutic benefits in moderate to severe Crohn’s disease (CD) with associated improvements in quality of life, endoscopic healing, and reduction in steroid use.2 After induction, infliximab is administered as maintenance therapy to maintain clinical remission. Drug concentrations may vary based on disease severity, inflammation, and other drug clearance mechanisms,3 and therefore therapeutic drug monitoring (TDM) is often needed to optimize dosing while also monitoring for antidrug antibodies.4 Infliximab dose escalation in patients with CD is recommended in the setting of waning clinical response and low drug trough levels. The need to dose escalate, however, does not necessarily represent a linear deterioration of disease but rather a transient process that requires a subsequent re-evaluation of the dose and frequency of drug administration....

Evolution of post-traumatic stress disorder and patient reported-outcomes during the COVID-19 pandemic among cancer patients of the French longitudinal COVIPACT study.

12123 Background: Sudden COVID-19 pandemic has enforced social restrictions across the globe, including social distancing, curfews and total lockdowns, which persist in many parts of the world. Beyond these measures, cancer patients have faced up to the threat of the risk of severe COVID-19 infections and the adaptations of medical oncology practices, with potential impact on their psychological well-being. We aimed to follow Post-Traumatic Stress Disorder (PTSD) symptoms and other Patient-Reported Outcomes (PROs) over this period among cancer patients from the French COVIPACT study. Methods: The COVIPACT study (NCT04366154) included patients with solid/hematologic malignancy receiving medical treatment during the first lockdown in outpatient departments of two cancer centers. Patients were asked to fulfill validated questionnaires on PTSD symptoms (IES-R), insomnia (ISI), quality of life (FACT-G) and cognition (FACT-Cog) at baseline (M0, first lockdown, Apr/May 2020), 3 months (M3, post-lockdown, Jul/Aug 2020) and 6 months (M6, second lockdown, Oct/Nov 2020). PTSD was defined as an IES-R score ≥33 and moderate/severe insomnia as an ISI score ≥15. Higher values on the FACT-G (range 0-108) and FACT-Cog (PCI subscale range 0-72) indicated better quality of life and cognition, respectively. Changes in PROs over time were assessed using mixed models for repeated measures. Results: Among the 734 patients included in COVIPACT, 579, 347 and 328 completed the questionnaires at M0, M3 and M6, respectively: median age, 64 years, 72% women, 59% metastatic status. Patients were mostly treated for breast (44%), lung, head and neck (20%), digestive (16%) and gynecologic cancers (11%). We observed a J-shaped evolution of PTSD over time, affecting 21.2% of patients during the first lockdown, 13.6% the post-lockdown and 23.6% during the second lockdown (p for time < 0.001). Moreover, patients reported linear deterioration of cognitive function over follow-up (p < 0.001). No change was observed in any dimension of quality of life (p for time = 0.06). 24.3%, 27.1% and 28.1% of the patients reported insomnia at M0,M3 and M6 (p for time = 0.35). At each time, PTSD was associated with more insomnia, worst quality of life and cognitive complain. At all the times, ≥50% of patients with PTSD reported insomnia compared to ≤23% in non-PTSD patients (p < 0.001). In addition, there was a clinically significant difference of ≥16 points on the FACT-G and ≥8 points on the FACT-Cog PCI between PTSD and non-PTSD patients (p < 0.001) at the all times. Conclusions: More than 20% of patients have developed PTSD during the different periods of lockdown, with strong association with poor quality of life, cognitive complain and insomnia. Psychosocial support promoting emotional resilience should be largely offered to cancer patients to prevent and/or reduce PTSD. Clinical trial information: NCT04366154.

Preventive Maintenance Model for National School Buildings in Indonesia Using a Constraint Programming Approach

The Indonesian government needs to maintain around 231,000 school buildings in active use. Such a portfolio of buildings given the diversity of locations, limited maintenance budget, and deterioration rates varied by different building conditions presents many challenges to effective maintenance planning. Many of those schools had been reported to be aging and in a degenerated condition. However, contemporary practice for the planning method of Indonesia’s building maintenance program applies reactive maintenance strategies with a single linear deterioration rate. Such methodology cannot properly guarantee the sustainability of those school buildings. Therefore, this study attempts to examine a different approach to Indonesia’s building maintenance planning by adopting a preventive maintenance strategy using the deterioration rate model proved by historical data from a previous study. This study develops an optimization model with varied deterioration rates and considers the budget limitation, by utilizing a Constraint Programming (CP) approach. The proposed model achieves the minimum maintenance cost for a real case of 41 school buildings under different deterioration rates to ensure adequate building conditions and maintain expected levels of service. Finally, research analysis also proves that this new preventive maintenance model has potential to deliver superior capability for assisting building maintenance decisions in Indonesia’s government.

712 Uterine contraction frequency in the last hour of labor: how many are too many?

ACOG defines the upper limit of normal uterine contraction frequency (UCF) at 5 per 10 minutes, averaged over 30 minutes. Others suggest 4/10 min as max. The choice has significant implications for maintaining progress in cervical dilatation while avoiding fetal deterioration. We compared the two cutoff points to predict postnatal outcomes (cord blood BE, pH, 5 min Apgar’s, prediction of BE≤ -12mMol/l, & neonatal recovery of FHR tachycardia at 16 min) and examined the implications of UCF over the last hour of labor before birth on them. We evaluate 475 cases from a unique research data set developed in the 1970’s by ANOVA and ROC. 346 fetuses had at least one 10-min period (last hour) with >4 UCF while there were 159 with >5 For both UCF>4 and >5, there were between-time-group differences in for almost all measures. (most p < .001) However, the patterns of worsening outcomes differed appreciably & consistently. For >4, there was an approximately linear deterioration in the last hour before birth correlating with duration of >4. For >5, however, slightly poorer outcomes were noted beginning even at < 20 minutes. They remained relatively stable until 40+ minutes of >5, but then outcomes worsened dramatically. (BE Fig 1) ROC showed >4 had better AUC for adverse outcomes (BE ≤-12 & NHR failure to recover). (Fig 2 recovery) What constitutes abnormal UCF has significant implications for predicting postnatal outcomes. Using the > 5 definition of abnormal masks impending compromise. Many at-risk cases read normal even with 40 minutes of increased UCF. However, when as a result of too many contractions fetal reserve is then depleted, sudden clinical deterioration can occur carrying over into the neonatal period. Using >4, vs. >5, demonstrated a gradual, predictable, and basically linear depletion of reserve with improved discrimination of risk. Recognizing deterioration earlier in the pathophysiology allows more time to assess and safely intervene. Thus, we believe the definition of increased uterine activity should be changed to an average of >4 UCF per 10 min period.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Population-based Tabu search with evolutionary strategies for permutation flow shop scheduling problems under effects of position-dependent learning and linear deterioration

This paper investigates permutation flow shop scheduling (PFSS) problems under the effects of position-dependent learning and linear deterioration. In a PFSS problem, there are n jobs and m machines in series. Jobs are separated into operations on m different machines in series, and jobs have to follow the same machine order with the same sequence. The PFSS problem under the effects of learning and deterioration is introduced with a mixed-integer nonlinear programming model. The time requirement for solving large-scale problems type of PFSS problem is exceedingly high. Therefore, well-known metaheuristic methods for the PFSS problem without learning and deterioration effects such as iterated greedy algorithms and discrete differential evolution algorithm are adapted for the problem with learning and deterioration effects in order to find a faster and near-optimal or optimal solution for the problem. Furthermore, this paper proposes a hybrid solution algorithm that is called population-based Tabu search algorithm (TSPOP) with evolutionary strategies such as crossover and mutation. The search algorithm is built on the basic structure of Tabu search and it searches for the best candidate from a solution population instead of improving the current best candidate at each iteration. Furthermore, the performances of these methods in view of solution quality are discussed in this paper by using test problems for 20, 50, and 100 jobs with 5, 10, 20 machines. Experimental results show that the proposed TSPOP algorithm outperforms the other existing algorithms in view of solution quality.

Gluten neuropathy: electrophysiological progression and HLA associations.

Gluten neuropathy (GN) is the term used to describe peripheral neuropathy that occurs in patients with gluten sensitivity (GS) or coeliac disease (CD) in the absence of other risk factors. We aimed to describe the neurophysiological progression rate of GN across time and look into the potential role of genetic susceptibility in its development. This is a cohort study of 45 patients with GN with a mean follow-up period of 8 ± 5years. The assessments included clinical and neurophysiological data and HLA-DQ genotyping. The mean age at diagnosis was 60 ± 12years. The majority of patients had a length-dependent neuropathy (75.6%), whereas the rest were diagnosed with sensory ganglionopathy (SG). DQA1*02-positive patients were more likely to suffer with SG compared to the DQA1*02 negative patients (60% versus 13.8%, p = 0.009). There was also a trend for statistical significance regarding the DQB1*06 allele and the DQA1*01/DQB1*06 haplotype were found more frequently in patients with GN than in healthy controls (p = 0.026 and p = 0.047, respectively). A linear effect of time on the neurophysiological findings was found in radial sensory nerve action potential (1.9% mean annual decrement, p = 0.036), sural sensory nerve action potential (3.3% mean annual decrement, p = 0.013) and tibial nerve motor compound action potential (6.5% mean annual decrement, p < 0.001) amplitudes, independently from age or gender. GN is a late manifestation of GS and CD. The majority of patients have the length-dependent neuropathy with a linear deterioration over time. HLA genotyping of GS and CD patients who suffer from neuropathic symptoms is recommended as it can help identifying patients at risk for developing SG.

A note: flowshop scheduling with linear deterioration and job-rejection

We study a scheduling problem on an $$m$$ -machine flowshop with linear deterioration of job processing times and job rejection. The objectives are minimum makespan and minimum total load, subject to an upper bound on the total permitted rejection cost. The problems are NP-hard (since the single machine makespan minimization version was shown to be hard), and we introduce pseudo-polynomial dynamic programming algorithms, thus proving that both problems are NP-hard in the ordinary sense.