Shortening Project Makespan in the Case of Resource Constraints and Activity Durations Uncertainty

2017 ◽  
Vol 6 (3) ◽  
pp. 26-36
Author(s):  
Игорь Царьков ◽  
Igor Tsarkov
Keyword(s):  
Project Scheduling ◽  
High Efficiency ◽  
Resource Constraints ◽  
Computational Results ◽  
Decision Points ◽  
Practice Activity ◽  
Expected Makespan

Shortening project expected makespan in the case of resource constraints is the most popular problem in project scheduling. But in practice activity durations is not determined. So the problem is to find a policy which could define which activity should be started at decision points to minimize expected project makespan. This problem usually called SRCPSP. In this paper we define key research tasks of such a problem and propose extended activity-based policy XABP. Computational results show us the high efficiency of this policy.

scholarly journals Scheduling Optimization of Prefabricated Construction Projects by Genetic Algorithm

2021 ◽  
Vol 11 (12) ◽  
pp. 5531
Author(s):  
Linlin Xie ◽  
Yajiao Chen ◽  
Ruidong Chang
Keyword(s):  
Project Scheduling ◽  
Construction Projects ◽  
Resource Constraints ◽  
Construction Project ◽  
Engineering Application ◽  
Project Schedule ◽  
Scheduling Optimization ◽  
Implementation Method ◽  
Traditional Construction ◽  
Construction Project Scheduling

Prefabricated buildings are the direction of the future development of the construction industry and have received widespread attention. The effective execution of prefabricated construction project scheduling should consider resource constraints and the supply arrangement of prefabricated components. However, the traditional construction resource-constrained project scheduling implementation method cannot simultaneously consider the characteristics of the linkage between component production and on-site assembly construction. It cannot also fully adapt to the scheduling implementation method of the prefabricated construction projects. It is difficult to work out a reasonable project schedule and resource allocation table. In order to determine the relevant schedule parameters that can reflect the actual construction situation of the prefabricated building and meet the scheduling requirements of the prefabricated project, this study proposes a prefabricated construction project scheduling model that considers project resource constraints and prefabricated component supply constraints. Additionally, it improves the design of traditional genetic algorithms (GAs). Research results of the experimental calculation and engineering application show that the proposed project scheduling optimization model and GA are effective and practical, which can help project managers in effectively formulating prefabricated construction project scheduling plans, reasonably allocating resources, reducing completion time, and improving project performance.

scholarly journals Triboelectric Effect Enabled Self-Powered, Point-of-Care Diagnostics: Opportunities for Developing ASSURED and REASSURED Devices

Micromachines ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 337
Author(s):  
Navneet Soin ◽  
Sam J. Fishlock ◽  
Colin Kelsey ◽  
Suzanne Smith
Keyword(s):  
High Efficiency ◽  
Resource Constraints ◽  
Point Of Care ◽  
Wearable Sensors ◽  
Middle Income ◽  
Physiological Signal ◽  
Point Of Care Diagnostics ◽  
Self Powered ◽  
Triboelectric Nanogenerators ◽  
Triboelectric Effect

The use of rapid point-of-care (PoC) diagnostics in conjunction with physiological signal monitoring has seen tremendous progress in their availability and uptake, particularly in low- and middle-income countries (LMICs). However, to truly overcome infrastructural and resource constraints, there is an urgent need for self-powered devices which can enable on-demand and/or continuous monitoring of patients. The past decade has seen the rapid rise of triboelectric nanogenerators (TENGs) as the choice for high-efficiency energy harvesting for developing self-powered systems as well as for use as sensors. This review provides an overview of the current state of the art of such wearable sensors and end-to-end solutions for physiological and biomarker monitoring. We further discuss the current constraints and bottlenecks of these devices and systems and provide an outlook on the development of TENG-enabled PoC/monitoring devices that could eventually meet criteria formulated specifically for use in LMICs.

A new project scheduling approach for improving multi-product multi-period production planning problems

2008 ◽  
Vol 222 (11) ◽  
pp. 1517-1527 ◽  
Author(s):  
S Noori ◽  
M Bagherpour ◽  
F Zorriassatine ◽  
A Makui ◽  
R Parkin
Keyword(s):  
Production Planning ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Simulation Analysis ◽  
Analytical Models ◽  
Hybrid Solutions ◽  
Demand Fluctuations ◽  
Feasible Solutions ◽  
Operational Criteria ◽  
Planning Problems

The problem of matching production levels for individual products to demand fluctuations during multiple periods is known in the production planning literature as the multi-product multi-period (MPMP) problem. Linear programming (LP)-based solutions have been extensively reported in this respect. MPMP problems are commonly solved by using either analytic or simulation methods. More recently, hybrid solutions consisting of both analytical models and simulation analysis have been proposed where some operational criteria, e.g. the order of visit to machining centres, are taken into account. In this paper, results related to some of the literature based on hybrid solutions are used as the initial feasible solutions and then examined in the context of project scheduling by considering the influences of resource constraints. After converting the MPMP to a project network problem and assigning resources to activities and consequently levelling the resource profiles, it is discovered that machine utilization can be further improved by applying unused machine capacities. A LP model is therefore developed in order to maximize feasible production rates over all the production planning periods. The proposed approach results in improvements on the results of earlier hybrid solutions reported in the literature. Finally, three different planning problems are suggested for further applications of the proposed approach in the context of manufacturing environments.

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