scholarly journals Shuffled Frog Leaping Algorithm for Preemptive Project Scheduling Problems with Resource Vacations Based on Patterson Set

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Yi Han ◽  
Ikou Kaku ◽  
Jianhu Cai ◽  
Yanlai Li ◽  
Chao Yang ◽  
...  
Keyword(s):  
Project Scheduling ◽  
Single Mode ◽  
Medium Size ◽  
Scheduling Problems ◽  
Shuffled Frog Leaping Algorithm ◽  
Scarce Resources ◽  
Splitting Number ◽  
Shuffled Frog Leaping ◽  
Project Scheduling Problem ◽  
Effectiveness And Efficiency

This paper presents a shuffled frog leaping algorithm (SFLA) for the single-mode resource-constrained project scheduling problem where activities can be divided into equant units and interrupted during processing. Each activity consumes 0–3 types of resources which are renewable and temporarily not available due to resource vacations in each period. The presence of scarce resources and precedence relations between activities makes project scheduling a difficult and important task in project management. A recent popular metaheuristic shuffled frog leaping algorithm, which is enlightened by the predatory habit of frog group in a small pond, is adopted to investigate the project makespan improvement on Patterson benchmark sets which is composed of different small and medium size projects. Computational results demonstrate the effectiveness and efficiency of SFLA in reducing project makespan and minimizing activity splitting number within an average CPU runtime, 0.521 second. This paper exposes all the scheduling sequences for each project and shows that of the 23 best known solutions have been improved.

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.

scholarly journals An Efficient Particle Swarm Optimizer with Application to Man-Day Project Scheduling Problems

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Ruey-Maw Chen ◽  
Frode Eika Sandnes
Keyword(s):  
Project Scheduling ◽  
Particle Swarm ◽  
Scheduling Problem ◽  
Np Hard ◽  
Scheduling Problems ◽  
Particle Swarm Optimizer ◽  
Np Hard Problem ◽  
Hard Problems ◽  
Project Scheduling Problem ◽  
Mode Assignment

The multimode resource-constrained project scheduling problem (MRCPSP) has been confirmed to be an NP-hard problem. Particle swarm optimization (PSO) has been efficiently applied to the search for near optimal solutions to various NP-hard problems. MRCPSP involves solving two subproblems: mode assignment and activity priority determination. Hence, two PSOs are applied to each subproblem. A constriction PSO is proposed for the activity priority determination while a discrete PSO is employed for mode assignment. A least total resource usage (LTRU) heuristic and minimum slack (MSLK) heuristic ensure better initial solutions. To ensure a diverse initial collection of solutions and thereby enhancing the PSO efficiency, a best heuristic rate (HR) is suggested. Moreover, a new communication topology with random links is also introduced to prevent slow and premature convergence. To verify the performance of the approach, the MRCPSP benchmarks in PSPLIB were evaluated and the results compared to other state-of-the-art algorithms. The results demonstrate that the proposed algorithm outperforms other algorithms for the MRCPSP problems. Finally, a real-world man-day project scheduling problem (MDPSP)—a MRCPSP problem—was evaluated and the results demonstrate that MDPSP can be solved successfully.

A Practical Algorithmic Approach Towards Multi-Modal Resource Constrained Multi-Project Scheduling Problems (MMRCMPSP)

2015 ◽  
Author(s):  
Michael Völker ◽  
Taiba Zahid ◽  
Thorsten Schmidt
Keyword(s):  
Project Scheduling ◽  
Decision Support Tool ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Decision Strategy ◽  
Resource Constrained ◽  
Support Tool ◽  
Decision Variables ◽  
Np Hard Problem ◽  
Project Scheduling Problem

The literature concerning resource constrained project scheduling problems (RCPSP) are mainly based on series or parallel schedule generation schemes with priority sequencing rules to resolve conflicts. Recently, these models have been extended for scheduling multi-modal RCPSP (MMRCPSP) where each activity has multiple possibilities to be performed thus providing decision managers a useful tool for manipulating resources and activities. Nonetheless, this further complicates the scheduling problem inflicted by increase of decision variables. Multiple heuristics have been proposed for this NP-hard problem. The main solution strategy adopted by such heuristics is a two loops decision strategy. Basically the problem is split between two parts where first part is conversion of MMRCPSP to RCPSP (mode fix) while second is finding feasible solution for a resource constrained project and is restricted to single project environments. This research aims on the development of scheduling heuristics, exploring the possibilities of scheduling MMRCPSP with parallel assignment of modes while sequencing the activities. The work addresses Multi-Mode Resource Constrained Multi-Project Scheduling Problem, (MMRCMPSP) by formulating a mathematical model that regards practical requirements of working systems. The algorithm is made intelligent and flexible in order to adopt and shift among various defined heuristic rules under different objectives to function as a decision support tool for managers.

scholarly journals On some implementations of solving the resource constrained project scheduling problems

2019 ◽  
Vol 29 (1) ◽  
pp. 31-42 ◽  
Author(s):  
E.Kh. Gimadi ◽  
E.N. Goncharov ◽  
D.V. Mishin
Keyword(s):  
Renewable Resources ◽  
Project Scheduling ◽  
Resource Constraints ◽  
Scheduling Problems ◽  
Makespan Minimization ◽  
Resource Constrained ◽  
Resource Constrained Project Scheduling ◽  
Project Scheduling Problem ◽  
Technological Constraints

We consider a resource-constrained project scheduling problem with respect to the makespan minimization criterion. The problem accounts for technological constraints of activities precedence together with resource constraints. Activities pre- emptions are not allowed. The problem with renewable resources is NP-hard in the strong sense. We propose an exact branch and bound algorithm for solving the problem with renewable resources. It uses our new branching scheme based on the representation of a schedule in form of the activity list. We use two approaches of constructing the lower bound. We present results of numerical experiments, illustrating the quality of the proposed lower bounds. The test instances are taken from the library of test instances PSPLIB.

scholarly journals An Enhanced Discrete Bees Algorithm for Resource Constrained Optimization Problems

2019 ◽  
Vol 22 (64) ◽  
pp. 123-134
Author(s):  
Mohamed Amine Nemmich ◽  
Fatima Debbat ◽  
Mohamed Slimane
Keyword(s):  
Project Scheduling ◽  
Optimization Problems ◽  
Solution Space ◽  
Bees Algorithm ◽  
Problem Instance ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Resource Constrained ◽  
Proposed Model ◽  
Project Scheduling Problem

In this paper, we propose a novel efficient model based on Bees Algorithm (BA) for the Resource-Constrained Project Scheduling Problem (RCPSP). The studied RCPSP is a NP-hard combinatorial optimization problem which involves resource, precedence, and temporal constraints. It has been applied to many applications. The main objective is to minimize the expected makespan of the project. The proposed model, named Enhanced Discrete Bees Algorithm (EDBA), iteratively solves the RCPSP by utilizing intelligent foraging behaviors of honey bees. The potential solution is represented by the multidimensional bee, where the activity list representation (AL) is considered. This projection involves using the Serial Schedule Generation Scheme (SSGS) as decoding procedure to construct the active schedules. In addition, the conventional local search of the basic BA is replaced by a neighboring technique, based on the swap operator, which takes into account the specificity of the solution space of project scheduling problems and reduces the number of parameters to be tuned. The proposed EDBA is tested on well-known benchmark problem instance sets from Project Scheduling Problem Library (PSPLIB) and compared with other approaches from the literature. The promising computational results reveal the effectiveness of the proposed approach for solving the RCPSP problems of various scales.

A Multi-Agent Optimization Method for Preemptive Resource-Constrained Project Scheduling

2019 ◽  
Vol 10 (1) ◽  
pp. 21-33
Author(s):  
Yongyi Shou ◽  
Wenjin Hu ◽  
Changtao Lai ◽  
Ying Ying
Keyword(s):  
Project Scheduling ◽  
Optimization Method ◽  
Negotiation Process ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Project Schedule ◽  
Resource Constrained ◽  
Resource Constrained Project Scheduling ◽  
Multi Agent ◽  
Project Scheduling Problem

A multi-agent optimization method is proposed to solve the preemptive resource-constrained project scheduling problem in which activities are allowed to be preempted no more than once. The proposed method involves a multi-agent system, a negotiation process, and two types of agents (activity agents and schedule agent). The activity agents and the schedule agent negotiate with each other to allocate resources and optimize the project schedule. Computational experiments were conducted using the standard project scheduling problem sets. Compared with prior studies, results of the proposed method are competitive in terms of project makespan. The method can be extended to other preemptive resource-constrained project scheduling problems.

Application and Evaluation of Bee-Based Algorithms in Scheduling

2018 ◽  
pp. 20-42
Author(s):  
Ayse Aycim Selam ◽  
Ercan Oztemel
Keyword(s):  
Project Scheduling ◽  
Optimal Solution ◽  
Benchmark Problems ◽  
Manufacturing Processes ◽  
Scheduling Problems ◽  
Hard Problems ◽  
Project Scheduling Problem ◽  
Multi Mode ◽  
Vital Element

Scheduling is a vital element of manufacturing processes and requires optimal solutions under undetermined conditions. Highly dynamic and, complex scheduling problems can be classified as np-hard problems. Finding the optimal solution for multi-variable scheduling problems with polynomial computation times is extremely hard. Scheduling problems of this nature can be solved up to some degree using traditional methodologies. However, intelligent optimization tools, like BBAs, are inspired by the food foraging behavior of honey bees and capable of locating good solutions efficiently. The experiments on some benchmark problems show that BBA outperforms other methods which are used to solve scheduling problems in terms of the speed of optimization and accuracy of the results. This chapter first highlights the use of BBA and its variants for scheduling and provides a classification of scheduling problems with BBA applications. Following this, a step by step example is provided for multi-mode project scheduling problem in order to show how a BBA algorithm can be implemented.

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