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

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.

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

Advances in Operations Research ◽

10.1155/2014/505716 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10 ◽

Cited By ~ 1

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.

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

Mathematical Problems in Engineering ◽

10.1155/2012/365697 ◽

2012 ◽

Vol 2012 ◽

pp. 1-18 ◽

Cited By ~ 10

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.

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

Mathematical Problems in Engineering ◽

10.1155/2014/634649 ◽

2014 ◽

Vol 2014 ◽

pp. 1-15 ◽

Cited By ~ 2

Author(s):

A. Shirzadeh Chaleshtarti ◽

S. Shadrokh ◽

Y. Fathi

Keyword(s):

Branch And Bound ◽

Project Scheduling ◽

Real Life ◽

Scheduling Problem ◽

Nonrenewable Resources ◽

Resource Constrained ◽

Resource Constrained Project Scheduling ◽

Branch And Bound Algorithms ◽

Project Scheduling Problem ◽

The Difference

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.

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