scholarly journals New Quantization Approach for the Anomaly: The Increase in Time Float following Consumption

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Zhixiong Su ◽  
Hanying Wei
Keyword(s):  
Project Scheduling ◽  
Optimal Solutions ◽  
Current Analysis ◽  
Resource Constrained ◽  
Project Duration ◽  
Maximum Duration ◽  
Time Parameters ◽  
Time Float ◽  
Plan Management ◽  
Generalized Precedence Relations

Anomalous scenarios in projects with generalized precedence relations (GPRs) have been arousing widely interest. A recent relevant discovery of anomaly under GPRs is that an activity’s time float increases following its consumption. The scenario is contrary to a common idea for plan management, and it also changes relationships between time floats and maximum prolongations of activity durations. Classic computations may be invalid to time parameters under GPRs. This study tests the fact that the current analysis on the anomaly has limitations so that it may provide improper guidelines for project scheduling and lead to undesirable effects. A new quantization algorithm is presented for the anomaly that overcomes the limitations of the current works. In particular, the algorithm confirms accurate time parameters and maximum duration prolongations of activities under constraints that retain project duration. The accuracy of quantization for the anomaly is particularly important for project scheduling with GPRs. Moreover, an application of the anomaly is developed in the resource-constrained project scheduling with activity splitting and GPRs, and an illustration is provided to test the fact that the new quantization result of the anomaly is an essential guarantee to achieve optimal solutions.

scholarly journals A branch and bound hybrid algorithm with four deterministic heuristics for the resource constrained project scheduling problem (RCPSP)

DYNA ◽  
2015 ◽  
Vol 82 (190) ◽  
pp. 198-207 ◽  
Author(s):  
Daniel Morillo Torres ◽  
Luis Fernando Moreno Velasquez ◽  
Francisco Javier Díaz Serna
Keyword(s):  
Branch And Bound ◽  
Project Scheduling ◽  
Search Tree ◽  
Feasible Region ◽  
Scheduling Problem ◽  
Optimal Solutions ◽  
Resource Constrained ◽  
Basic Algorithm ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem

This paper addresses the Resource Constrained Project Scheduling Problem (RCPSP). For its solution, a hybrid methodology, which uses a Branch and Bound basic algorithm with dominance rules, is developed and implemented, and is combined with four deterministic heuristics whose objective is to prune the search tree branches, taking into account the iterations available and, at the same time, to minimize the probability of discarding branches that contain optimal solutions. Essentially, these strategies allow the allocation of most iterations to the most promissory regions in an organized manner using only subsets with similar or the same characteristics as those of the optimal solutions at each level of the tree, thus assuring a broad search within the feasible region and, simultaneously, a good exploitation by the selective use of the subsets by level. Finally, the developed algorithm performance is analyzed by solving some of the problems of the PSPLIB test library.

scholarly journals Comparison of Heuristic Priority Rules in the Solution of the Resource-Constrained Project Scheduling Problem

2021 ◽  
Vol 13 (17) ◽  
pp. 9956
Author(s):  
Osman Hürol Türkakın ◽  
David Arditi ◽  
Ekrem Manisalı
Keyword(s):  
Resource Allocation ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Priority Rules ◽  
Resource Constrained ◽  
Start Time ◽  
Project Duration ◽  
Resource Constrained Project Scheduling ◽  
Finish Time ◽  
Positional Weight

Resource-constrained project scheduling (RCPS) aims to minimize project duration under limited resource availabilities. The heuristic methods that are often used to solve the RCPS problem make use of different priority rules. The comparative merits of different priority rules have not been discussed in the literature in sufficient detail. This study is a response to this research gap. It compares 17 heuristic priority rules and seeks the best performing heuristic priority rule. This is the first study ever that compares heuristic priority rules by considering combinations of variations in (1) resource allocation procedures, (2) number of activities, (3) number of resource constraints, and (4) resource supply levels. The objective is to understand the relative merits of heuristic rules used in solving the RCPS problem. The findings indicate that the “minimum late finish time” rule generates the shortest predicted project duration when used in parallel resource allocation, whereas the “minimum late start time”, “minimum late finish time”, and the “highest rank of positional weight 2” rules perform best in serial resource allocation. It was also found that parallel resource allocation is slightly superior to serial resource allocation in most instances.

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