scholarly journals A Modified PSO Algorithm for Minimizing the Total Costs of Resources in MRCPSP

2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Mohammad Khalilzadeh ◽  
Fereydoon Kianfar ◽  
Ali Shirzadeh Chaleshtari ◽  
Shahram Shadrokh ◽  
Mohammad Ranjbar
Keyword(s):  
Project Scheduling ◽  
Renewable Resource ◽  
Pso Algorithm ◽  
Scheduling Problem ◽  
Due Dates ◽  
Resource Constrained ◽  
Nonrenewable Resource ◽  
Penalty Cost ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem

We introduce a multimode resource-constrained project scheduling problem with finish-to-start precedence relations among project activities, considering renewable and nonrenewable resource costs. We assume that renewable resources are rented and are not available in all periods of time of the project. In other words, there is a mandated ready date as well as a due date for each renewable resource type so that no resource is used before its ready date. However, the resources are permitted to be used after their due dates by paying penalty costs. The objective is to minimize the total costs of both renewable and nonrenewable resource usage. This problem is called multimode resource-constrained project scheduling problem with minimization of total weighted resource tardiness penalty cost (MRCPSP-TWRTPC), where, for each activity, both renewable and nonrenewable resource requirements depend on activity mode. For this problem, we present a metaheuristic algorithm based on a modified Particle Swarm Optimization (PSO) approach introduced by Tchomté and Gourgand which uses a modified rule for the displacement of particles. We present a prioritization rule for activities and several improvement and local search methods. Experimental results reveal the effectiveness and efficiency of the proposed algorithm for the problem in question.

Preemptive multi-skilled resource constrained project scheduling problem with hard/soft interval due dates

2019 ◽  
Vol 53 (5) ◽  
pp. 1877-1898
Author(s):  
Hamidreza Maghsoudlou ◽  
Behrouz Afshar-Nadjafi ◽  
Seyed Taghi Akhavan Niaki
Keyword(s):  
Project Scheduling ◽  
Real Life ◽  
Scheduling Problem ◽  
Due Dates ◽  
Resource Constrained ◽  
Due Date ◽  
Setup Cost ◽  
Resource Constrained Project Scheduling ◽  
Processing Cost ◽  
Project Scheduling Problem

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.

The R-PSO algorithm solving multi-skill resource-constrained project scheduling problem

2021 ◽  
pp. 71-82
Author(s):  
Dang Quoc Huu
Keyword(s):  
Project Scheduling ◽  
Optimal Solution ◽  
Simulated Data ◽  
Pso Algorithm ◽  
Scheduling Problem ◽  
Resource Constrained ◽  
Feasible Schedule ◽  
Approximate Methods ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem

The Multi-Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP) is a combinational optimization problem with many applications in science and practical areas. This problem aims to find out the feasible schedule for the completion of projects and workflows that is minimal duration or cost (or both of them - multi objectives). The researches show that MS-RCPSP is classified into NP-Hard classification, which could not get the optimal solution in polynomial time. Therefore, we usually use approximate methods to carry out the feasible schedule. There are many publication results for that problem based on evolutionary methods such as GA, Greedy, Ant, etc. However, the evolutionary algorithms usually have a limitation that is fallen into local extremes after a number of generations. This paper will study a new method to solve the MS-RCPSP problem based on the Particle Swarm Optimization (PSO) algorithm that is called R-PSO. The new improvement of R-PSO is re-assigning the resource to execute solution tasks. To evaluate the new algorithm's effectiveness, the paper conducts experiments on iMOPSE datasets. Experimental results on simulated data show that the proposed algorithm finds a better schedule than related works.

A Novel Heuristic Algorithm for Spatial Resource Constrained Project Scheduling Problem

2011 ◽  
Vol 58-60 ◽  
pp. 1448-1453
Author(s):  
Xiao Guang Yu ◽  
De Chen Zhan ◽  
Lan Shun Nie
Keyword(s):  
Project Scheduling ◽  
Heuristic Method ◽  
Renewable Resource ◽  
Scheduling Problem ◽  
Resource Constrained ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem ◽  
Block Based ◽  
Scheduling Heuristic ◽  
Spatial Resource Allocation

Spatial resources such as slipway and erection platform are key and bottleneck resources for large equipment manufacturing enterprises, and restrict output and efficiency of enterprises. Spatial resource has several distinct features, such asspatiality,divisibility,adjacency,exclusivityandgroupcharacteristic. These features introduce great complexities into spatial Resource Constrained Project Scheduling Problem (sRCPSP), which lead sRCPSP very hard to model and solve. So a mathematical model for sRCPSP considered all features and other renewable resource constrains comprehensively has been established. Then an Activity Type Priority based Serial Scheduling heuristic method and a Resource-Time Block based Spatial Resource Allocation Method have been proposed to solve the model. Results of numerical experiments proved that those two algorithms are correct and effective.

scholarly journals Resource Constrained Project Scheduling Subject to Due Dates: Preemption Permitted with Penalty

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Behrouz Afshar-Nadjafi
Keyword(s):  
Project Scheduling ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Due Dates ◽  
Resource Constrained ◽  
Setup Cost ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem ◽  
Total Project Cost ◽  
Total Project

Extensive research works have been carried out in resource constrained project scheduling problem. However, scarce researches have studied the problems in which a setup cost must be incurred if activities are preempted. In this research, we investigate the resource constrained project scheduling problem to minimize the total project cost, considering earliness-tardiness and preemption penalties. A mixed integer programming formulation is proposed for the problem. The resulting problem is NP-hard. So, we try to obtain a satisfying solution using simulated annealing (SA) algorithm. The efficiency of the proposed algorithm is tested based on 150 randomly produced examples. Statistical comparison in terms of the computational times and objective function indicates that the proposed algorithm is efficient and effective.

A RESOURCE OPTIMISATION BASED HEURISTIC FOR RESOURCE CONSTRAINED PROJECT SCHEDULING PROBLEM

2019 ◽  
Vol XVI (4) ◽  
pp. 115-124
Author(s):  
Mazhar Ali ◽  
Saif Ullah ◽  
Mirza Jahanzaib
Keyword(s):  
Project Scheduling ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Resource Constrained ◽  
Shared Resources ◽  
Penalty Cost ◽  
Scarce Resources ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem ◽  
And Shifts

Resource constrained project scheduling problem has significant application in industries. Although several heuristic solutions have been developed in the literature to address this problem, most of these have lesser focus on scheduling of shared and scarce resources. The presented study proposes a resource optimisation based heuristic (ROBH) to optimise the utilisation of shared resources so as to minimise the penalty cost of projects. The proposed ROBH identifies shared resources within the project activities and shifts the activities from the bottleneck resource to the residual resources. The performance of the proposed ROBH was tested using the standard benchmark instances of project scheduling problems available in the existing literature. The results were compared with those obtained from the heuristics available in the project scheduling problem library. This comparison indicated that the results provided by ROBH are significant as compared to the results obtained from the heuristics available in the literature.

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