A Parallel Branch and Bound Algorithm for the Resource Leveling Problem with Minimal Lags

[EN] The efficient use of resources is a key factor to minimize the cost while meeting time deadlines and quality requirements; this is especially important in construction projects where field operations take fluctuations of resources unproductive and costly. Resource Leveling Problems (RLP) aim to sequence the construction activities that maximize the resource consumption efficiency over time, minimizing the variability. Exact algorithms for the RLP have been proposed throughout the years to offer optimal solutions; however, these problems require a vast computational capability ( combinatorial explosion ) that makes them unpractical. Therefore, alternative heuristic and metaheuristic algorithms have been suggested in the literature to find local optimal solutions, using different libraries to benchmark optimal values; for example, the Project Scheduling Problem LIBrary for minimal lags is still open to be solved to optimality for RLP. To partially fill this gap, the authors propose a Parallel Branch and Bound algorithm for the RLP with minimal lags to solve the RLP with an acceptable computational effort. This way, this research contributes to the body of knowledge of construction project scheduling providing the optimums of 50 problems for the RLP with minimal lags for the first time, allowing future contributors to benchmark their heuristics meth-ods against exact results by obtaining the distance of their solution to the optimal values. Furthermore, for practitioners,the time required to solve this kind of problem is reasonable and practical, considering that unbalanced resources can risk the goals of the construction project.This research was supported by the FAPA program of the Universidad de Los Andes (Colombia). The authors would like to thank the research group of Construction Engineering and Management (INgeco), especially J. S. Rojas-Quintero, and the Department of Systems Engineering at the Universidad de Los Andes. The authors are also grateful to the anonymous reviewers for their valuable and constructive suggestions.Ponz Tienda, JL.; Salcedo-Bernal, A.; Pellicer Armiñana, E. (2017). A Parallel Branch and Bound Algorithm for the Resource Leveling Problem with Minimal Lags. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING. 32:474-498. doi:10.1111/mice.12233S47449832Adeli, H. (2000). High-Performance Computing for Large-Scale Analysis, Optimization, and Control. Journal of Aerospace Engineering, 13(1), 1-10. doi:10.1061/(asce)0893-1321(2000)13:1(1)ADELI, H., & KAMAL, O. (2008). Parallel Structural Analysis Using Threads. Computer-Aided Civil and Infrastructure Engineering, 4(2), 133-147. doi:10.1111/j.1467-8667.1989.tb00015.xAdeli, H., & Kamal, O. (1992). Concurrent analysis of large structures—II. applications. Computers & Structures, 42(3), 425-432. doi:10.1016/0045-7949(92)90038-2Adeli, H., Kamat, M. 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A survey of variants and extensions of the resource-constrained project scheduling problem

The resource-constrained project scheduling problem (RCPSP) consists of activities that must be scheduled subject to precedence and resource constraints such that the makespan is minimized. It has become a well-known standard problem in the context of project scheduling which has attracted numerous researchers who developed both exact and heuristic scheduling procedures. However, it is a rather basic model with assumptions that are too restrictive for many practical applications. Consequently, various extensions of the basic RCPSP have been developed. This paper gives an overview over these extensions. The extensions are classified according to the structure of the RCPSP. We summarize generalizations of the activity concept, of the precedence relations and of the resource constraints. Alternative objectives and approaches for scheduling multiple projects are discussed as well. In addition to popular variants and extensions such as multiple modes, minimal and maximal time lags, and net present value-based objectives, the paper also provides a survey of many less known concepts. --project scheduling,modeling,resource constraints,temporal constraints,networks

Improved Adaptive Harmony Search algorithm for the resource levelling problem with minimal lags

The resource leveling problem (RLP) aims to provide the most efficient resource consumption as well as minimize the resource fluctuations without increasing the prescribed makespan of the construction project. Resource fluctuations are impractical, inefficient and costly when they happen on construction sites. Therefore, previous research has tried to find an efficient way to solve this problem. Metaheuristics using Harmony Search seem to be faster and more efficient than others, but present the same problem of premature convergence closing around local optimums. In order to diminish this issue, this study introduces an innovative Improved and Adaptive Harmony Search (IAHS) algorithm to improve the solution of the RLP with multiple resources. This IAHS algorithm has been tested with the standard Project Scheduling Problem Library for four metrics that provide different levelled profiles from rectangular to bell shapes. The results have been compared with the benchmarks available in the literature presenting a complete discussion of results. Additionally, a case study of 71 construction activities contemplating the widest possible set of conditions including continuity and discontinuity of flow relationships has been solved as example of application for real life construction projects. Finally, a visualizer tool has been developed to compare the effects of applying different metrics with an app for Excel. The IAHS algorithm is faster with better overall results than other metaheuristics. Results also show that the IAHS algorithm is especially fitted for the Sum of Squares Optimization metric. The proposed IAHS algorithm for the RLP is a starting point in order to develop user-friendly and practical computer applications to provide realistic, fast and good solutions for construction project managers.This research was partially supported by the FAPA program of Universidad de Los Andes, Colombia (code P14.246922.005/01). The authors would also like to thank the research group of Construction Engineering and Management (INgeco).Ponz Tienda, JL.; Salcedo-Bernal, A.; Pellicer Armiñana, E.; Benlloch Marco, J. (2017). Improved Adaptive Harmony Search algorithm for the resource levelling problem with minimal lags. Automation in Construction. 77:82-92. https://doi.org/10.1016/j.autcon.2017.01.018S82927

An overview of recent research results and future research avenues using simulation studies in project management

This paper gives an overview of three simulation studies in dynamic project scheduling integrating baseline scheduling with risk analysis and project control. This integration is known in the literature as dynamic scheduling. An integrated project control method is presented using a project control simulation approach that combines the three topics into a single decision support system. The method makes use of Monte Carlo simulations and connects schedule risk analysis (SRA) with earned value management (EVM). A corrective action mechanism is added to the simulation model to measure the efficiency of two alternative project control methods. At the end of the paper, a summary of recent and state-of-the-art results is given, and directions for future research based on a new research study are presented

The Resource Leveling Problem with multiple resources using an adaptive genetic algorithm

Resource management ensures that a project is completed on time and at cost, and that its quality is as previously defined; nevertheless, resources are scarce and their use in the activities of the project leads to conflicts in the schedule. Resource Leveling Problems consider how to make the resource consumption as efficient as possible. This paper presents a new Adaptive Genetic Algorithm for the Resource Leveling Problem with multiple resources, and its novelty lies in using the Weibull distribution to establish an estimation of the global optimum as a termination condition. The extension of the project deadline with a penalty is allowed, avoiding the increase in the project criticality punishing the shift of activities. The algorithmis tested with the standard Project Scheduling Problem Library PSPLIB, and a complete analysis and benchmarking test instances are presented. The proposed algorithm is implemented using VBA for Excel 2010 in order to provide a flexible and powerful decision support system that enables practitioners to choose between different feasible solutions to a problem, and in addition it is easily adjustable to the constraints and particular needs of each project in realistic environments.This study was partially funded by the Spanish Ministry of Science and Innovation (research project BIA2011-23602).Ponz Tienda, JL.; Yepes Piqueras, V.; Pellicer Armiñana, E.; Moreno Flores, J. (2013). The Resource Leveling Problem with multiple resources using an adaptive genetic algorithm. Automation in Construction. 29(1):161-172. doi:10.1016/j.autcon.2012.10.003S16117229

The Multimode Resource Constrained Project Scheduling Problem for Repetitive Activities in Construction Projects

[EN] In construction projects, resource availability might limit the implementation of ideal schedules. Especially, when repetitive activities are involved, traditional resource¿constrained project scheduling problem (RCPSP) models fail to allocate the resource consumption in an efficient manner. Besides, actual models only provide local optimal solutions and do not incorporate activity acceleration routines. To fulfill this gap, partially, a mathematical optimization model, the multimode RCPSP for repetitive activities in construction projects, is proposed and solved to optimality; it takes into account acceleration routines under real construction scenarios using spreadsheets. The article shows a complete computational experimentation over a real construction project, considering several scenarios of resource availabilities and continuity conditions. The model allows analyzing the resources efficiency indexes comparing them to resource consumptions, continuity of activities, and objective functions that reveal that fragmented activities do not provide better resource efficiency outcomes.This research was partially supported by the FAPA program of Universidad de Los Andes, Colombia (code P14.246922.005/01). The authors would also like to thank the research group of Construction Engineering and Management (INgeco) at Universidad de los Andes.García-Nieves, J.; Ponz-Tienda, JL.; Salcedo-Bernal, A.; Pellicer Armiñana, E. (2018). The Multimode Resource Constrained Project Scheduling Problem for Repetitive Activities in Construction Projects. Computer-Aided Civil and Infrastructure Engineering. 33(8):655-671. https://doi.org/10.1111/mice.12356S65567133

A Decision Support System for Dynamic Integrated Project Scheduling and Equipment Operation Planning

Common practice in scheduling under limited resource availability is to first schedule activities with the assumption of unlimited resources, and then assign required resources to activities until available resources are exhausted. The process of matching a feasible resource plan with a feasible schedule is called resource allocation. Then, to avoid sharp fluctuations in the resource profile, further adjustments are applied to both schedule and resource allocation plan within the limits of feasibility constraints. This process is referred to as resource leveling in the literature. Combination of these three stages constitutes the standard approach of top-down scheduling. In contrast, when scarce and/or expensive resource is to be scheduled, first a feasible and economical resource usage plan is established and then activities are scheduled accordingly. This practice is referred to as bottom-up scheduling in the literature. Several algorithms are developed and implemented in various commercial scheduling software packages to schedule based on either of these approaches. However, in reality resource loaded scheduling problems are somewhere in between these two ends of the spectrum. Additionally, application of either of these conventional approaches results in just a feasible resource loaded schedule which is not necessarily the cost optimal solution. In order to find the cost optimal solution, activity scheduling and resource allocation problems should be considered jointly. In other words, these two individual problems should be formulated and solved as an integrated optimization problem. In this research, a novel integrated optimization model is proposed for solving the resource loaded scheduling problems with concentration on construction heavy equipment being the targeted resource type. Assumptions regarding this particular type of resource along with other practical assumptions are provided for the model through inputs and constraints. The objective function is to minimize the fraction of the execution cost of resource loaded schedule which varies based on the selected solution and thus, considered to be the model's decision making criterion. This fraction of cost which hereafter is referred to as operation cost, encompasses four components namely schedule delay cost, shipping, rental and ownership costs for equipment