Advancements in Optimization and Resource Allocation

The field of optimization and resource allocation is witnessing significant developments, with a focus on addressing complex problems in stochastic environments, multi-agent systems, and dynamic resource allocation. Researchers are exploring innovative approaches, such as adjusted processing time frameworks, QUBO formulations, and iterative VCG-based mechanisms, to improve operational efficiency and cooperation in various domains. Noteworthy papers in this area include those that propose novel frameworks for team formation, multi-regional network design, and coflow scheduling, as well as studies on the relationship between team-optimal solutions and Nash equilibria. Notable papers:

  • A QUBO Framework for Team Formation: introduces a unified TeamFormation formulation that captures all cost definitions for team formation problems.
  • Iterative VCG-based Mechanism Fosters Cooperation in Multi-Regional Network Design: proposes a mechanism for multi-regional network design that fosters cooperation among subnetwork operators.
  • Performance bounds for priority-based stochastic coflow scheduling: establishes a bound on the approximation ratio of a priority policy with respect to the optimal priority policy for arbitrary probability distributions of flow sizes.

Sources

Assembly line balancing considering stochastic task times and production defects

A QUBO Framework for Team Formation

Iterative VCG-based Mechanism Fosters Cooperation in Multi-Regional Network Design

Deviation Between Team-Optimal Solution and Nash Equilibrium in Flow Assignment Problems

Performance bounds for priority-based stochastic coflow scheduling

Simulation of Autonomous Industrial Vehicle Fleet Using Fuzzy Agents: Application to Task Allocation and Battery Charge Management

Remember, but also, Forget: Bridging Myopic and Perfect Recall Fairness with Past-Discounting

Local Computation Algorithms for Knapsack: impossibility results, and how to avoid them

Generalized Assignment and Knapsack Problems in the Random-Order Model

Budget-Feasible Contracts

Distributed Resource Allocation for Human-Autonomy Teaming under Coupled Constraints

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