Resource Leveling of an Industrial Building Using Genetic Algorithm Technique

Construction companies should schedule their projects in a manner that considers theefficient use of limited resources in order to complete a project within estimated budget, onschedule and in compliance with the specifications. In this context, the planning of resourcesbecomes crucial for a construction project, which can be accomplished by resource leveling.Resource leveling - also known as resource smoothing - is a method that attempts to reducethe fluctuations in resource usage in order to make the resource requirements as uniform aspossible while maintaining the original project duration. The studies dealing with resource leveling problems can be classified into two categories, which are; (1) analytical methods and(2) heuristic methods. Analytical methods may give optimal solutions on small-scaledproblems; however, they are inadequate in large-scaled problems. As a result of theweaknesses of analytical methods, many studies have been conducted in order to developmore efficient models by heuristic methods. Genetic algorithm-based resource leveling is oneof these models, which is developed to attain better solutions. The main objective of thisstudy is to handle the resource leveling problem of an industrial building using geneticalgorithms. In this context, a schedule for an industrial building is established using theCritical Path Method (CPM). The information about the logical constraints and the resourcesrequired to carry out activities were obtained through the interviews with civil engineers fromthe company, whose expertise is on industrial buildings. The proposed genetic algorithmbased resource leveling model attempts to improve the schedule. The developed modelprovided a decrease of 20% in the total resource-days required to complete the project. Thestudy is of benefit to participants of construction industry, because it makes them aware of the potential use of the combination of critical path method and genetic algorithms in order to solve the resource leveling problem

Providing a Suitable Model for Solving Resource Leveling in Project Management

Resource leveling and resource Allocation are main tasks of project management. The aim of project scheduling is allocating resources to activities while faced on minimizing some economic objectives. In particular, in resource leveling problems the objective is to minimize a function of the resource utilization over time. If there is no restriction on the amount of available resources, raised the issue of resource leveling is required to fluctuations in resource utilization decreases without increasing the project duration. In this paper for managing transportation resource leveling problem, especially when based on multiple objective function of NP-hard problems, has been used Genetic Algorithm. This method is inspired from nature, presented as well as the desired resolution and optimal solutions. The results indicated that the genetic algorithm is able to respond very well at a reasonable offer

Balancing labor requirements in a manufacturing environment

“This research examines construction environments within manufacturing facilities, specifically semiconductor manufacturing facilities, and develops a new optimization method that is scalable for large construction projects with multiple execution modes and resource constraints. The model is developed to represent real-world conditions in which project activities do not have a fixed, prespecified duration but rather a total amount of work that is directly impacted by the level of resources assigned. To expand on the concept of resource driven project durations, this research aims to mimic manufacturing construction environments by allowing a non-continuous resource allocation to project tasks. This concept allows for resources to shift between projects in order to achieve the optimal result for the project manager. Our model generates a novel multi-objective resource constrained project scheduling problem. Specifically, two objectives are studied; the minimization of the total direct labor cost and the minimization of the resource leveling. This research will utilize multiple techniques to achieve resource leveling and discuss the advantage each one provides to the project team, as well as a comparison of the Pareto Fronts between the given resource leveling and cost minimization objective functions. Finally, a heuristic is developed utilizing partial linear relaxation to scale the optimization model for large scale projects. The computation results from multiple randomly generated case studies show that the new heuristic method is capable of generating high quality solutions at significantly less computational time”--Abstract, page iv

Optimizing Multiple-Resources Leveling in Multiple Projects Using Discrete Symbiotic Organisms Search

Resource leveling is used in project scheduling to reduce fluctuation in resource usage over the period of project implementation. Fluctuating resource usage frequently creates the untenable requirement of regularly hiring and firing temporary staff to meet short-term project needs. Construction project decision makers currently rely on experience-based methods to manage fluctuations. However, these methods lack consistency and may result in unnecessary waste of resources or costly schedule overruns. This research introduces a novel discrete symbiotic organisms search for optimizing multiple resources leveling in the multiple projects scheduling problem (DSOS-MRLMP). The optimization model proposed is based on a recently developed metaheuristic algorithm called symbiotic organisms search (SOS). SOS mimics the symbiotic relationship strategies that organisms use to survive in the ecosystem. Experimental results and statistical tests indicate that the proposed model obtains optimal results more reliably and efficiently than do the other optimization algorithms considered. The proposed optimization model is a promising alternative approach to assisting project managers in handling MRLMP effectively