scholarly journals A MATHEMATICAL MODEL FOR DYNAMIC PROJECT SCHEDULING PROBLEM AND REACTIVE SCHEDULING IMPLEMENTATION

2020 ◽  
Vol 8 (4) ◽  
pp. 83-97
Author(s):  
Murat RUHLUSARAÇ ◽  
Filiz ÇALIŞKAN
Keyword(s):  
Project Scheduling ◽  
Resource Constraints ◽  
Programming Model ◽  
Real Life ◽  
Dynamic Environment ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Baseline Schedule ◽  
Dynamic Events ◽  
Project Scheduling Problem

In today's real-life implementations, projects are executed under uncertainty in a dynamic environment. In addition to resource constraints, the baseline schedule is affected due to the unpredictability of the dynamic environment. Uncertainty-based dynamic events experienced during project execution may change the baseline schedule partially or substantially and require projects' rescheduling. In this study, a mixed-integer linear programming model is proposed for the dynamic resource-constrained project scheduling problem. Three dynamic situation scenarios are solved with the proposed model, including machine breakdown, worker sickness, and electricity power cut. Finally, generated reactive schedules are completed later than the baseline schedule.

scholarly journals Solving the nuclear dismantling project scheduling problem by combining mixed-integer and constraint programming techniques and metaheuristics

2021 ◽  
Author(s):  
Felix Hübner ◽  
Patrick Gerhards ◽  
Christian Stürck ◽  
Rebekka Volk
Keyword(s):  
Constraint Programming ◽  
Project Scheduling ◽  
Computational Study ◽  
Real Life ◽  
Mixed Integer ◽  
Extensive Literature ◽  
Scheduling Problem ◽  
Multiple Modes ◽  
Project Scheduling Problem ◽  
Optimisation Techniques

AbstractScheduling of megaprojects is very challenging because of typical characteristics, such as expected long project durations, many activities with multiple modes, scarce resources, and investment decisions. Furthermore, each megaproject has additional specific characteristics to be considered. Since the number of nuclear dismantling projects is expected to increase considerably worldwide in the coming decades, we use this type of megaproject as an application case in this paper. Therefore, we consider the specific characteristics of constrained renewable and non-renewable resources, multiple modes, precedence relations with and without no-wait condition, and a cost minimisation objective. To reliably plan at minimum costs considering all relevant characteristics, scheduling methods can be applied. But the extensive literature review conducted did not reveal a scheduling method considering the special characteristics of nuclear dismantling projects. Consequently, we introduce a novel scheduling problem referred to as the nuclear dismantling project scheduling problem. Furthermore, we developed and implemented an effective metaheuristic to obtain feasible schedules for projects with about 300 activities. We tested our approach with real-life data of three different nuclear dismantling projects in Germany. On average, it took less than a second to find an initial feasible solution for our samples. This solution could be further improved using metaheuristic procedures and exact optimisation techniques such as mixed-integer programming and constraint programming. The computational study shows that utilising exact optimisation techniques is beneficial compared to standard metaheuristics. The main result is the development of an initial solution finding procedure and an adaptive large neighbourhood search with iterative destroy and recreate operations that is competitive with state-of-the-art methods of related problems. The described problem and findings can be transferred to other megaprojects.

A Resource Constrained Project Scheduling Problem With Multi-Modes

2020 ◽  
Vol 11 (1) ◽  
pp. 55-70 ◽  
Author(s):  
Cansu Altintas ◽  
Meral Azizoglu
Keyword(s):  
Project Scheduling ◽  
Mixed Integer Linear Programming ◽  
Programming Model ◽  
Renewable Resource ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Resource Requirement ◽  
Project Completion ◽  
Variable Elimination ◽  
Project Scheduling Problem

In this study, the authors consider a project scheduling problem with a single non-renewable resource. The authors assume that the resource is released at scheduled times and specified quantities and the resource is consumed at activity completion. The activities can be processed at different modes where a mode is defined by a processing time and a resource requirement amount. The problem is to select the modes and timings of the activities so as to minimize the project completion time. The authors give a mixed integer linear programming model and discuss some variable elimination mechanisms to enhance its efficiency.

scholarly journals Model and Algorithm for Human Resource-Constrained R&D Program Scheduling Optimization

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Junjie Chen ◽  
Shurong Tong ◽  
Hongmei Xie ◽  
Yafei Nie ◽  
Jingwen Zhang
Keyword(s):  
Project Scheduling ◽  
Optimization Problems ◽  
Programming Model ◽  
Mixed Integer ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Resource Constrained ◽  
Enumeration Algorithm ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem

In resource-constrained project scheduling problems, renewable resources can be expanded into human resources with competency differences. A flexible resource-constrained project scheduling problem with competency differences is proposed, which is a practical extension close to Research and Development (R&D) program management, from the traditional multimode resource-constrained project scheduling problem. A parameter and estimation formula to measure staff competency is presented, and a mixed-integer programming model is established for the problem. The single-objective optimization problems of optimal duration and optimal cost are solved sequentially according to the biobjective importance. To solve the model, according to the assumptions and constraints of the model, the initial network diagram of multiple projects is determined, the enumeration algorithm satisfying constraint conditions provides the feasible solution sets, and the algorithm based on dynamic programming is designed for phased optimization. Experimental results show that the proposed optimization model considering competence differences can solve the problem effectively.

scholarly journals Constraint Programming-Based Transformation Approach for a Multi-Objective & Multi-Mode Resource Investment Project Scheduling Problem Under Mixed Fuzzy-Stochastic Uncertainties

2021 ◽  
Author(s):  
Kemal Subulan ◽  
Gizem Çakır
Keyword(s):  
Constraint Programming ◽  
Project Scheduling ◽  
Real Life ◽  
Investment Project ◽  
Scheduling Problem ◽  
Multi Objective ◽  
Resource Investment ◽  
Transformation Approach ◽  
Project Scheduling Problem ◽  
Multi Mode

Abstract In fuzzy mathematical programming literature, most of the transformation approaches were mainly focused on integer linear programs (ILPs) with fuzzy parameters/variables. However, these ILP-based solution approaches may be inadequate for solving large-scaled combinatorial fuzzy optimization problems, like project scheduling under fuzzy-stochastic environments. Moreover, many project scheduling applications may contain different types of uncertainties such as fuzziness, stochasticity, dynamism etc. simultaneously in real-life settings. Based on these motivations, this paper presents a novel constraint programming (CP) based transformation approach for solving a multi-objective and multi-mode fuzzy-stochastic resource investment project scheduling problem (FS-MRIPSP) which is a well-known NP-complete problem. In fact, the proposed solution approach mainly depends on a bound & decomposition principle which divides fuzzy components of the problem into crisp middle, lower and upper level problems. Thus, it reduces the problem dimension and does not need to use any standard fuzzy arithmetic and ranking operations directly. Furthermore, stochastic nature of the problem is also taken into account by using a multi-scenario based stochastic programming technique. Finally, a weighted additive fuzzy goal program (WAFGP) is embedded into the proposed CP-based transformation approach in order to produce compromise fuzzy project schedules which trade-off between the expected values of project makespan and total resource usage costs. To show validity and practicality of the proposed approach, a real-life application is also presented for a production-and-operations management (POM) module implementation process of an international Enterprise Resource Planning (ERP) software. The generated fuzzy project schedules under different scenarios by the proposed CP-based approach are also compared to the results of a similar ILP-based transformation approach. Computational results have shown that the proposed CP-based approach outperforms than the ILP-based approach in terms of both solution quality and computational time.

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