Constraint programming-based transformation approach for a mixed fuzzy-stochastic resource investment project scheduling problem

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

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.

scholarly journals A Priority Rule-Based Heuristic for Resource Investment Project Scheduling Problem with Discounted Cash Flows and Tardiness Penalties

2009 ◽  
Vol 2009 ◽  
pp. 1-10 ◽  
Author(s):  
Amir Abbas Najafi ◽  
Fatemeh Azimi
Keyword(s):  
Project Scheduling ◽  
Net Present Value ◽  
Heuristic Method ◽  
Investment Project ◽  
Cash Flows ◽  
Scheduling Problem ◽  
Solution Approach ◽  
Resource Investment ◽  
Project Scheduling Problem ◽  
Resource Investment Problem

Resource investment problem with discounted cash flows (RIPDCFs) is a class of project scheduling problem. In RIPDCF, the availability levels of the resources are considered decision variables, and the goal is to find a schedule such that the net present value of the project cash flows optimizes. In this paper, we consider a new RIPDCF in which tardiness of project is permitted with defined penalty. We mathematically formulated the problem and developed a heuristic method to solve it. The results of the performance analysis of the proposed method show an effective solution approach to the problem.

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 Constraint-Based Approach for Multi-Skilled Project Scheduling Problem

2014 ◽  
Vol 681 ◽  
pp. 265-269
Author(s):  
Yan Li ◽  
Zhi Run Xiao
Keyword(s):  
Constraint Programming ◽  
Project Scheduling ◽  
Complex Problem ◽  
Programming Approach ◽  
Scheduling Problem ◽  
Computational Results ◽  
Resource Assignment ◽  
Software Company ◽  
Scheduling Model ◽  
Project Scheduling Problem

The problem of multi-skilled project scheduling (MSPSP) is a complex problem of task scheduling and resource assignment that comes up in the daily management of many software company. In this paper we present a constraint programming (CP) approach for the MSPSP. We extend the project scheduling literature by developing a project scheduling model that accounts for differing skills among workers. The computational results for the MSPSP show that the constraint programming approach increases the performance of the model solving processes. The results for the MSPSP is effective in solving the proposed problem.

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