scholarly journals Branch and Bound Algorithms for Resource Constrained Project Scheduling Problem Subject to Nonrenewable Resources with Prescheduled Procurement

2014 ◽  
Vol 2014 ◽  
pp. 1-15 ◽  
Author(s):  
A. Shirzadeh Chaleshtarti ◽  
S. Shadrokh ◽  
Y. Fathi

A lot of projects in real life are subject to some kinds of nonrenewable resources that are not exactly similar to the type defined in the project scheduling literature. The difference stems from the fact that, in those projects, contrary to the common assumption in the project scheduling literature, nonrenewable resources are not available in full amount at the beginning of the project, but they are procured along the project horizon. In this paper, we study this different type of nonrenewable resources. To that end, we extend the resource constrained project scheduling problem (RCPSP) by this resource type (RCPSP-NR) and customize four basic branch and bound algorithms of RCPSP for it, including precedence tree, extension alternatives, minimal delaying alternatives, and minimal forbidden sets. Several bounding and fathoming rules are introduced to the algorithms to shorten the enumeration process. We perform comprehensive experimental analysis using the four customized algorithms and also CPLEX solver.

DYNA ◽  
2015 ◽  
Vol 82 (190) ◽  
pp. 198-207 ◽  
Author(s):  
Daniel Morillo Torres ◽  
Luis Fernando Moreno Velasquez ◽  
Francisco Javier Díaz Serna

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.


2019 ◽  
Vol 53 (5) ◽  
pp. 1877-1898
Author(s):  
Hamidreza Maghsoudlou ◽  
Behrouz Afshar-Nadjafi ◽  
Seyed Taghi Akhavan Niaki

This paper considers a preemptive multi-skilled resource constrained project scheduling problem in a just-in-time environment where each activity has an interval due date to be completed. In this problem setting, resuming a preempted activity requires an extra setup cost, while each time unit violation from the given due date incurs earliness or tardiness penalty. Also, processing cost of each skill to execute any activity depends on the assigned staff member to accomplish the skill. The objective function of the model aims to minimize the total cost of allocating staff to skills, earliness–tardiness penalties and preemption costs. Two integer formulations are proposed for the model which are compared in terms of number of variables, constraints and elapsed run-time to optimality. Furthermore, an ant colony based metaheuristic is developed to tackle real life scales of the proposed model. This algorithm relies on two intelligent local search heuristics. Parameters of the algorithm are calibrated using Taguchi method. The results of the experiments for the proposed algorithm confirm that the proposed algorithm has satisfying performance.


2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Behrouz Afshar-Nadjafi ◽  
Zeinab Khalaj ◽  
Esmaeil Mehdizadeh

We study resource constrained project scheduling problem with respect to resource leveling as objective function and allowance of preemption in activities. The branch and bound algorithms proposed in previous researches on resource leveling problem do not consider preemption. So, representing a model for the problem, a branch and bound algorithm is proposed. This algorithm can handle preemption in resource leveling problem. Comparing the resource leveling problem and the preemptive resource leveling problem, it is observed that considering preemption in the problem leads to better results in the objective function. This improvement imposes additional time to solve the problem. Coding the algorithm in MATLAB and checking it on the projects with 8 and 10 activities, results show that the proposed algorithm is efficient.


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