Bismark Singh Lower bounds on minimization problems are essential for convergence of both branching-based and iterative solution methods for optimization problems. They are also required for evaluating the quality of feasible solutions by providing conservative optimality gaps. We provide an analytical lower bound for a class of quadratic optimization problems with binary decision variables. In contrast to … Read more
We introduce the prime programming problem as a subclass of integer programming. These optimization models impose the restriction of feasible solutions being prime numbers. Then, we demonstrate how several classical problems in number theory can be formulated as prime programs. To solve such problems with a commercial optimization solver, we extend the branch-and-bound procedure of … Read more
In a recent work, Schmitt and Singh propose a new quadratic facility location model to address ecological challenges faced by policymakers in Bavaria, Germany. Building on this previous work, we significantly extend our understanding of this new problem. We develop connections to traditional combinatorial optimization models and show the problem is NP-hard. We then develop … Read more
Published in Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-031-47859-8_26 Lagrangian relaxation schemes, coupled with a subgradient procedure, are frequently employed to solve chance-constrained optimization models. The subgradient procedure typically relies on a step-size update rule. Although there is extensive research on the properties of these step-size update rules, there is little consensus on which rules are … Read more
Published in INFORMS Journal on Computing. https://doi.org/10.1007/978-3-031-47859-8_26 Typically, within facility location problems, fairness is defined in terms of accessibility of users. However, for facilities perceived as undesirable by communities hosting them, fairness between the usage of facilities becomes especially important. Limited research exists on this notion of fairness. To close this gap, we develop a series … Read more
We consider the problem of laying out several objects in an equal number of pre-defined positions. Objects are allowed finitely many orientations, can overlap each other, and must be arranged contiguously. We are particularly interested in the case when the evaluation of the dimensions of the objects requires computational or physical effort. We develop a … Read more
Published in Annals of Operations Research. https://doi.org/10.1007/978-3-031-47859-8_26 Motivated by a routing problem faced by banks to enhance their encashment services in the city of Perm, Russia, we solve versions of the traveling salesman problem with clustering. To minimize the risk of theft, suppliers seek to operate multiple vehicles and determine an efficient routing; and, a single vehicle serves … Read more
Published in Journal of Global Optimization. https://doi.org/10.1007/s10898-021-01041-y We develop a stochastic optimization model for scheduling a hybrid solar-battery storage system. Solar power in excess of the promise can be used to charge the battery, while power short of the promise is met by discharging the battery. We ensure reliable operations by using a joint chance … Read more