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Multi-Project Scheduling and Resource Allocation Report


Resource allocation and multi-project scheduling are essential for the efficient functionality of many companies. The distinctive feature of the modern business world is multi-tasking. A variety of projects and tasks are executed at the same time due to the need to meet all requirements, deadlines and satisfy growing demands. There are cases when available resources are not enough for a particular task. Consequently, there is a need for proper time management and division of resources. In the following paper, the efficiency of heuristics approaches for multi-project scheduling and resource allocation will be evaluated and analyzed.

As it has been already mention, there are situations when the availability of necessary resources is limited. As a result, the decision-making process should focus on the proper organization of resources. Besides, many companies work on several projects simultaneously. It means that the scarcity of resources is even more pressing. When such a situation occurs, one may observe the example of the need for multi-project scheduling and resource allocation. Resource allocation is the proper division of labor force and technological resources. Taking into consideration the constraints of resources, project managers mostly refer to heuristic methods as the most effective for multi-project scheduling (Lova and Tormos 263). Heuristic methods stand for attainable and optional solutions for particular problems. The basis for heuristic methods is clear — conduct the most urgent tasks first. There are various types of heuristic methods as far as their implementation and efficiency may vary depending on the urgency of tasks and type of project.

Meredith and Mantel take the hierarchical approach to plan projects as an example to address the problem of heuristics. This method is efficient as far as it presupposes the decomposition of all tasks. Thus, there are sub-tasks and one primary goal. In such an approach, the decision concerning the usage of resources depends on the estimated impact of one action on another (Meredith and Mantel, 414).

Yang and Fu have appraised the method of task priority. In their study, they analyze the effectiveness of the critical chain project management (CCPM) and evidence reasoning (ER) in the Chinese automobile R&D process. The authors emphasize the significance of the task priority and not project priority. This heuristic method has particular advantages. Thus, parallel technology transfer is an efficient way to allocate resources. There is always a threat due to the uncertainty of the multi-project schedule. Yang and Fu state that CCPM and ER are useful for the elimination of uncertainty (176).

Laslo and Goldberg, who evaluate matrix structure as an approach to multi-tasking and resource allocation, have addressed the issue of uncertainty in detail. Matrix structure presupposes the distribution of tasks of various projects among people or resources with particular skills. This technique is useful for a timely solution to the most urgent tasks in all projects. However, the disadvantage concerns conflicts between managers. Laslo and Goldberg suggest that conflicts are inevitable until all managers protect purely project-based goals and not the interests of the organization (785).

Finally, heuristic methods may not be useful in particular settings. Browning and Yassine have investigated these issues. Authors find out that such heuristic methods as MINSLK or MAXTWK do not perform well under peculiar circumstances. The authors evaluated twenty priority rules in more than ten thousand test problems. Results have shown that managers often face difficulty in choosing the appropriate heuristic method for decision-making (Browning and Yassine 212). Thus, heuristics is a useful tool for multi-project scheduling and resource allocation only when the manager knows the target aims and ways of their accomplishment. A random choice of priority rule does not help.

Works Cited

Browning, Tyson, and Ali Yassine. “Resource-constrained multi-project scheduling: priority rule revisited.” International Journal of Production Economics 126.2 (2010): 212-218. Print.

Laslo, Zohar, and Albert Goldberg. “Resource allocation under uncertainty in a multi-project matrix environment.” International Journal of Project Management 26.1(2008): 773-788. Print.

Lova, Antonio, and Pilar Tormos. “Analysis of scheduling schemes and heuristic rulesperformance in resource-constrained multi-project scheduling.” Annals of Operation Research 102.1 (2001): 263-286. Print.

Meredith, Jack, and Samuel Mantel. Project Management. Hoboken, New Jersey: John Wiley & Sons, 2009. Print.

Yang, Shanlin, and Lei Fu. “Critical chain and evidence reasoning applied to multi- project resource schedule in automobile R&D process.” International Journal of Project Management 32.1 (2014): 166-177. Print.

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IvyPanda. (2020, June 28). Multi-Project Scheduling and Resource Allocation. Retrieved from https://ivypanda.com/essays/multi-project-scheduling-and-resource-allocation/

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IvyPanda. "Multi-Project Scheduling and Resource Allocation." June 28, 2020. https://ivypanda.com/essays/multi-project-scheduling-and-resource-allocation/.

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IvyPanda. 2020. "Multi-Project Scheduling and Resource Allocation." June 28, 2020. https://ivypanda.com/essays/multi-project-scheduling-and-resource-allocation/.

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IvyPanda. (2020) 'Multi-Project Scheduling and Resource Allocation'. 28 June.

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