Optimization of resource allocation and leveling using genetic algorithms

Hegazy, T (1999) Optimization of resource allocation and leveling using genetic algorithms. Journal of Construction Engineering and Management, 125(3), pp. 167-175. ISSN 0733-9364

Abstract

Resource allocation and leveling are among the top challenges in project management. Due to the complexity of projects, resource allocation and leveling have been dealt with as two distinct subproblems solved mainly using heuristic procedures that cannot guarantee optimum solutions. In this paper, improvements are proposed to resource allocation and leveling heuristics, and the Genetic Algorithms (GAs) technique is used to search for near-optimum solution, considering both aspects simultaneously. In the improved heuristics, random priorities are introduced into selected tasks and their impact on the schedule is monitored. The GA procedure then searches for an optimum set of tasks' priorities that produces shorter project duration and better-leveled resource profiles. One major advantage of the procedure is its simple applicability within commercial project management software systems to improve their performance. With a widely used system as an example, a macro program is written to automate the GA procedure. A case study is presented and several experiments conducted to demonstrate the multiobjective benefit of the procedure and outline future extensions.

Item Type: Article
Index terms: duration, project management, resource allocation, heuristic, case study, project management software, program, complexity, guarantee, genetic algorithm, experiment
Subjects: systems engineering, project controls, project management theory and practice, contract structure, algorithms, software systems, resource management, digital technology, risk assessment, data collection methods
Topics: Digital Applications, Time Control, Site Management, Research Practice, Project Management, Engineering Principles, Risk Management, Procurement
Descriptive scope: 3 PCE

N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here