A mathematical model is presented for studying the effects of interactions among team members on the process of replacing members of a team in an organization. The model provides the ability to control the number of members that interact with each individual on the team. Through the use of analysis and computer simulations, it is shown how the amount of interaction affects the tradeoff between the expected performance and the number of replacements and interviews needed to find a good team using various replacement policies. New managerial insights into this process---such as the fact that it is not necessarily optimal to replace the worst-performing team member---are provided.team replacement, team building, NK model, complex systems
Mathematical models are presented for studying the value of leadership in a team where the members interact with each other. The models are based on a leader's role of motivating each team member to perform closer to his/her maximum ability. These models include controllable parameters whose values reflect the amount of task interdependence among the workers as well as the motivational skill and variability in the skill of the leader. Confirming results-such as the fact that the skill level of the leader is a critical factor in the expected performance of the team-establish credibility in the models. Mathematical analysis and computer simulations are used to provide new managerial insights into the value of the leader-such as the fact that the skill of the leader can be more important than controlling the amount of interdependence among the team members and that having a choice of multiple leaders with no particular motivating skill is beneficial to the performance of small teams but not to large teams.
T ruckload carriers are constantly faced with the problem of shipping full truckloads of goods at minimum cost between pairs of cities or customers, using a fleet of trucks located at one or more depots. In this paper, a new branch-and-bound algorithm for solving an integer-programming formulation of this vehicle-routing problem (VRP) with full truckloads is developed. The algorithm also takes into consideration the time-window constraints and waiting costs. The resulting efficiency, validated by computational tests on random problems, is due to a column-generation scheme that exploits the special structure of the problem to solve the linear-programming relaxation problems that arise at the nodes.
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