Lattice protein models are well studied abstractions of globular proteins. By discretizing the structure space and simplifying the energy model over regular proteins, they enable detailed studies of protein structure formation and evolution. But even in the simplest lattice protein models, the prediction of optimal structures is computationally hard. Therefore, often heuristic approaches are ap...

This paper points out that the treatment of utility maximization in current textbooks on microeconomic theory is deficient in at least three respects: breadth of coverage, completeness-cum-coherence of solution methods and mathematical correctness. Improvements are suggested in the form of a Kuhn-Tucker type theorem that has been customized for microeconomics. To ensure uniqueness of the optima...

This paper reviews, extends and analyzes a new class of penalty methods for nonlinear optimization. These methods adjust the penalty parameter dynamically; by controlling the degree of linear feasibility achieved at every iteration, they promote balanced progress toward optimality and feasibility. In contrast with classical approaches, the choice of the penalty parameter ceases to be a heuristi...

Packing rings into a minimum number of rectangles is an optimization problem which appears naturally in the logistics operations of the tube industry. It encompasses two major difficulties, namely the positioning of rings in rectangles and the recursive packing of rings into other rings. This problem is known as the Recursive Circle Packing Problem (RCPP). We present the first exact method for ...

Drone delivery is drawing increasing attention in last-mile delivery. Effective solution methods to solve decision-making problems arising drone allow run and assess systems. In this paper, we focus on systems with a single traditional vehicle multiple drones working tandem fulfill customer requests. We address the Traveling Salesman Problem Multiple Drones (TSP-MD) investigate modeling challen...