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The construction industry in the United States and other parts of the world has been facing several challenges, including a shortage of skilled workers. A review of the relevant body of knowledge indicates that one of the key reasons for this problem is the absence of human resource management strategies for construction workers at project, corporate, regional, or industry levels. This paper addresses the issues of workforce training and allocation on construction projects. It presents a framework to optimize the investment in, and to make the best use of, the available workforce with the intent to reduce project costs and improve schedule performance. A linear program model, entitled the Optimal Workforce Investment Model, is built to provide an optimization-based framework for matching supply and demand of construction labor most efficiently through training, recruitment, and allocation. Given a project schedule or demand profile and the available pool of workers, the suggested model provides human resource managers a combined strategy for training the available workers and hiring additional workers. The input data to the proposed model consists of a certain available labor pool, cost figures for training workers in different skills, the cost of hiring workers, hourly labor wages, and estimates of affinities between the different considered skills. The objective of the model is to minimize labor costs while satisfying project labor demands. Results from application of the model to typical situations are presented, and recommendations for future developments are made. [ABSTRACT FROM AUTHOR]

We describe a large-scale linear programming model for optimizing strategic (intercontinental) airlift capability. The model routes cargo and passengers through a specified transportation network with a given fleet of aircraft subject to many physical and policy constraints. The time-dynamic model captures a significant number of the important aspects of an airlift system in a large-scale military deployment, including aerial refueling, tactical (intercontinental) aircraft shuttles, and constraints based on crew availability. The model is designed to provide insight into issues associated with designing and operating an airlift system. We describe analyses for the U.S. Air Force system concerning fleet modernization and concerning the allocation of resources that affect the processing capacity of airfields. [ABSTRACT FROM AUTHOR]

Handling uncertainty in natural inflow is an important part of a hydroelectric scheduling model. In a stochastic programming formulation, natural inflow may be modeled as a random vector with known distribution, but the size of the resulting mathematical program can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such problems. We develop an enhanced Benders decomposition algorithm for solving multistage stochastic linear programs. The enhancements include warm start basis selection, preliminary cut generation, the multicut procedure, and decision tree traversing strategies. Computational results are presented for a collection of stochastic hydroelectric scheduling problems. [ABSTRACT FROM AUTHOR]