Dynamic Opportunistic Maintenance Scheduling for Series Systems Based on Theory of Constraints (TOC)–VLLTW Methodology

2016 ◽  
Vol 139 (2) ◽  
Author(s):  
Xinyang Tao ◽  
Tangbin Xia ◽  
Lifeng Xi
Keyword(s):  
Economic System ◽  
Time Window ◽  
Time Windows ◽  
Lag Time ◽  
Maintenance Scheduling ◽  
Theory Of Constraints ◽  
Opportunistic Maintenance ◽  
Maintenance Schedules ◽  
Series Systems

This paper focuses on series systems' dynamic opportunistic maintenance scheduling. Based on the machine-level predictive maintenance (PdM) method, a novel TOC–VLLTW methodology combined theory of constraints (TOC) policy and variable lead-lag time window (VLLTW) policy is proposed. The TOC policy provides machines' priorities according to their PdM durations to decrease system downtime when scheduling opportunistic maintenance. The VLLTW policy provides variable lead-lag time windows against different machines, allowing for more flexible and economic system opportunistic maintenance schedules. This proposed methodology is demonstrated through the case study based on the collected reliability information from a quayside container system. The results can effectively prove the effectiveness of the TOC–VLLTW methodology.

Simultaneous scheduling of maintenance crew and maintenance tasks in bus operating companies: a case study

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rodrigo Martins ◽  
Francisco Fernandes ◽  
Virginia Infante ◽  
Antonio R. Andrade
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Programming Model ◽  
Maintenance Scheduling ◽  
Linear Programming Model ◽  
Integer Linear Programming Model ◽  
Content Type ◽  
Maintenance Schedules ◽  
Operating Company

PurposeThe purpose of this paper is to describe an integer linear programming model to schedule the maintenance crew and the maintenance tasks in a bus operating company.Design/methodology/approachThe proposed methodology relies on an integer linear programming model that finds feasible maintenance schedules. It minimizes the costs associated with maintenance crew and the costs associated with unavailability. The model is applied in a real-world case study of a Portuguese bus operating company. A constructive heuristic approach is put forward, based on solving the maintenance scheduling problem for each bus separately.FindingsThe heuristic finds better solutions than the exact methods (based on branch-and-bound techniques) in a much lower computational time.Practical implicationsThe results suggest the relevance of such heuristic approaches for maintenance scheduling in practice.Originality/valueThis proposed model is an effective decision-making support method that provides feasible maintenance schedules for the maintenance technicians and for the maintenance tasks in a fleet of buses. It also complies with several operational, technical and labour constraints.

scholarly journals Path Optimization Model for Intra-City Express Delivery in Combination with Subway System and Ground Transportation

2019 ◽  
Vol 11 (3) ◽  
pp. 758
Author(s):  
Laijun Zhao ◽  
Xiaoli Wang ◽  
Johan Stoeter ◽  
Yan Sun ◽  
Huiyong Li ◽  
...  
Keyword(s):  
Optimization Model ◽  
Time Window ◽  
Time Windows ◽  
Path Optimization ◽  
Delivery Time ◽  
Basic Scenario ◽  
Study Results ◽  
Subway System ◽  
Express Delivery

Combined conventional ground transport with a subway system for line-haul transport for intra-city express delivery is a new transportation mode. Subway transportation can be used in the line-haul transportation of intra-city express delivery services to reduce cost, improve efficiency, raise customer satisfaction, and alleviate road congestion and air pollution. To achieve this, we developed a path optimization model (POM) with time windows for intra-city express delivery, which makes use of the subway system. Our model integrated the subway system with ground transportation in order to minimize the total delivery time. It considered the time window requirements of the senders and the recipients, and was constrained by the frequency of trains on the subway line. To solve the POM, we designed a genetic algorithm. The model was tested in a case study of a courier company in Shanghai, China. Meanwhile, based on the basic scenario, the corresponding solutions of the four different scenarios of the model are carried out. Then, we further analyzed the influence of the number of vehicles, the frequency of trains on the subway line, and the client delivery time window on the total delivery time, client time window satisfaction, and courier company costs based on the basic scenario. The results demonstrated that the total delivery time and the total time outside the time window decreased as the number of vehicles increased; the total delivery time and the total time outside the time window decreased as the delivery frequency along the subway line increased; the total delivery time and the total time outside the time window decreased as the sender’s time window increased. However, when the sender’s time window increased beyond a certain threshold, the total delivery time and the total time outside the time window no longer decreased greatly. The case study results can guide courier companies in path optimization for intra-city express delivery vehicles in combination with the subway network.

scholarly journals Exploration of the data space via trans-dimensional sampling: the case study of seismic double difference data

2021 ◽  
Author(s):  
Nicola Piana Agostinetti ◽  
Giulia Sgattoni
Keyword(s):  
Seismic Data ◽  
Time Window ◽  
Time Windows ◽  
Correlation Coefficients ◽  
Double Difference ◽  
Seismicity Rate ◽  
Data Space ◽  
Double Differences ◽  
Time Invariant

Abstract. Double differences (DD) seismic data are widely used to define elasticity distribution in the Earth's interior, and its variation in time. DD data are often pre-processed from earthquakes recordings through expert-opinion, where couples of earthquakes are selected based on some user-defined criteria, and DD data are computed from the selected couples. We develop a novel methodology for preparing DD seismic data based on a trans-dimensional algorithm, without imposing pre-defined criteria on the selection of couples of events. We apply it to a seismic database recorded on the flank of Katla volcano (Iceland), where elasticity variations in time has been indicated. Our approach quantitatively defines the presence of changepoints that separate the seismic events in time-windows. Within each time-window, the DD data are consistent with the hypothesis of time-invariant elasticity in the subsurface, and DD data can be safely used in subsequent analysis. Due to the parsimonious behavior of the trans-dimensional algorithm, only changepoints supported by the data are retrieved. Our results indicate that: (a) retrieved changepoints are consistent with first-order variations in the data (i.e. most striking changes in the DD data are correctly reproduced in the changepoint distribution in time); (b) changepoint locations in time do correlate neither with changes in seismicity rate, nor with changes in waveforms similarity (measured through the cross-correlation coefficients); and (c) noteworthy, the changepoint distribution in time seems to be insensitive to variations in the seismic network geometry during the experiment. Our results proofs that trans-dimensional algorithms can be positively applied to pre-processing of geophysical data before the application of standard routines (i.e. before using them to solve standard geophysical inverse problems) in the so called exploration of the data space.

scholarly journals PROPOSED PROCEDURE FOR OPTIMAL MAINTENANCE SCHEDULING UNDER EMERGENT FAILURES

2020 ◽  
Vol 26 (4) ◽  
pp. 396-409
Author(s):  
Abbas Al-Refaie ◽  
Heba Al-Shalaldeh ◽  
Natalija Lepkova
Keyword(s):  
Real Time ◽  
Optimization Procedure ◽  
Maintenance Scheduling ◽  
Optimization Models ◽  
Real Case ◽  
Production Lines ◽  
Free Margin ◽  
Optimal Maintenance ◽  
Maintenance Schedules

Production lines are usually subjected to emergent machine failures. Such emergent failures disrupt pre-established maintenance schedules, which challenge maintenance engineers to react to those failures in real time. This research proposes an optimization procedure for optimizing scheduling repairs of emergent failures. Three optimization models are developed. Model I schedules failures in newly idle repair shops with the objective of maximizing the number of scheduled repairs. Model II maximizes the number of assigned repairs to untapped ranges. Model III maximizes both the number of assigned failure repairs and satisfaction on regular and emergency repairs by resequencing regular and emergent failures in the shop that contains the largest free margin. A real case study is provided to illustrate the proposed optimization procedure. Results reveal that the proposed models efficiently scheduled and sequenced emergent failures in the idle maintenance shops, the untapped ranges between repairs of regular failures, and in the maintenance shop with the largest free margin. In conclusions, the proposed models can greatly support maintenance engineers in planning repairs under unexpected failures.

scholarly journals A hybrid ant colony algorithm based on multiple strategies for the vehicle routing problem with time windows

2021 ◽  
Author(s):  
Hongguang Wu ◽  
Yuelin Gao ◽  
Wanting Wang ◽  
Ziyu Zhang
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Ant Colony Algorithm ◽  
Time Window ◽  
Time Windows ◽  
Ant Colony ◽  
Routing Problem ◽  
Multiple Strategies ◽  
Hard Time ◽  
Mutation Operation

AbstractIn this paper, we propose a vehicle routing problem with time windows (TWVRP). In this problem, we consider a hard time constraint that the fleet can only serve customers within a specific time window. To solve this problem, a hybrid ant colony (HACO) algorithm is proposed based on ant colony algorithm and mutation operation. The HACO algorithm proposed has three innovations: the first is to update pheromones with a new method; the second is the introduction of adaptive parameters; and the third is to add the mutation operation. A famous Solomon instance is used to evaluate the performance of the proposed algorithm. Experimental results show that HACO algorithm is effective against solving the problem of vehicle routing with time windows. Besides, the proposed algorithm also has practical implications for vehicle routing problem and the results show that it is applicable and effective in practical problems.

scholarly journals The last-mile vehicle routing problem with delivery options

OR Spectrum ◽  
2021 ◽  
Author(s):  
Christian Tilk ◽  
Katharina Olkis ◽  
Stefan Irnich
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Resource Constraints ◽  
Time Window ◽  
Time Windows ◽  
Service Level ◽  
Optimal Solutions ◽  
Routing Problem ◽  
Common Location ◽  
Delivery Options

AbstractThe ongoing rise in e-commerce comes along with an increasing number of first-time delivery failures due to the absence of the customer at the delivery location. Failed deliveries result in rework which in turn has a large impact on the carriers’ delivery cost. In the classical vehicle routing problem (VRP) with time windows, each customer request has only one location and one time window describing where and when shipments need to be delivered. In contrast, we introduce and analyze the vehicle routing problem with delivery options (VRPDO), in which some requests can be shipped to alternative locations with possibly different time windows. Furthermore, customers may prefer some delivery options. The carrier must then select, for each request, one delivery option such that the carriers’ overall cost is minimized and a given service level regarding customer preferences is achieved. Moreover, when delivery options share a common location, e.g., a locker, capacities must be respected when assigning shipments. To solve the VRPDO exactly, we present a new branch-price-and-cut algorithm. The associated pricing subproblem is a shortest-path problem with resource constraints that we solve with a bidirectional labeling algorithm on an auxiliary network. We focus on the comparison of two alternative modeling approaches for the auxiliary network and present optimal solutions for instances with up to 100 delivery options. Moreover, we provide 17 new optimal solutions for the benchmark set for the VRP with roaming delivery locations.

scholarly journals Impact of COVID-19 pandemic on HIV viremia: a single-center cohort study in northern Italy

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Ilaria Izzo ◽  
Canio Carriero ◽  
Giulia Gardini ◽  
Benedetta Fumarola ◽  
Erika Chiari ◽  
...  
Keyword(s):  
Time Window ◽  
Time Windows ◽  
Continuum Of Care ◽  
Northern Italy ◽  
Hiv Diagnosis ◽  
Hiv Patients ◽  
Before And After ◽  
Missed Visits ◽  
Hiv Continuum Of Care ◽  
The Impact

Abstract Background Brescia Province, northern Italy, was one of the worst epicenters of the COVID-19 pandemic. The division of infectious diseases of ASST (Azienda Socio Sanitaria Territoriale) Spedali Civili Hospital of Brescia had to face a great number of inpatients with severe COVID-19 infection and to ensure the continuum of care for almost 4000 outpatients with HIV infection actively followed by us. In a recent manuscript we described the impact of the pandemic on continuum of care in our HIV cohort expressed as number of missed visits, number of new HIV diagnosis, drop in ART (antiretroviral therapy) dispensation and number of hospitalized HIV patients due to SARS-CoV-2 infection. In this short communication, we completed the previous article with data of HIV plasmatic viremia of the same cohort before and during pandemic. Methods We considered all HIV-patients in stable ART for at least 6 months and with at least 1 available HIV viremia in the time window March 01–November 30, 2019, and another group of HIV patients with the same two requisites but in different time windows of the COVID-19 period (March 01–May 31, 2020, and June 01–November 30, 2020). For patients with positive viremia (PV) during COVID-19 period, we reported also the values of viral load (VL) just before and after PV. Results: the percentage of patients with PV during COVID-19 period was lower than the previous year (2.8% vs 7%). Only 1% of our outpatients surely suffered from pandemic in term of loss of previous viral suppression. Conclusions Our efforts to limit the impact of pandemic on our HIV outpatients were effective to ensure HIV continuum of care.

Study on Vehicle Logistics Routing Path Problem with Time Windows Based on Particle Swarm Optimization

2014 ◽  
Vol 687-691 ◽  
pp. 5161-5164
Author(s):  
Lian Zhou Gao
Keyword(s):  
Particle Swarm Optimization ◽  
World Economy ◽  
Time Window ◽  
Time Windows ◽  
Particle Swarm ◽  
Modern Logistics ◽  
Swarm Optimization ◽  
Logistics Industry ◽  
Search Speed ◽  
Simulation Results

As the development of world economy, how to realize the reasonable vehicle logistics routing path problem with time window constrain is the key issue in promoting the prosperity and development of modern logistics industry. Through the research of vehicle logistics routing path 's demand, particle swarm optimization with a novel particle presentation is designed to solve the problem which is improved, effective and adept to the normal vehicle logistics routing. The simulation results of example indicate that the algorithm has more search speed and stronger optimization ability.

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