A method for finding all roots of a system of nonlinear equations is described. Our method makes use of C-GRASP, a recently proposed continuous global optimization heuristic. Given a nonlinear system, we solve a corresponding adaptively modified global optimization problem multiple times, each time using C-GRASP, with areas of repulsion around roots that have already … Read more
Network migration scheduling is the problem where inter-nodal traffic from an outdated telecommunications network is to be migrated to a new network. Nodes are migrated, one at each time period, from the old to the new network. All traffic originating or terminating at given node in the old network is moved to a specific node … Read more
Adverse drug reactions (ADRs) are estimated to be one of the leading causes of death. Many national and international agencies have set up databases of ADR reports for the express purpose of determining the relationship between drugs and adverse reactions that they cause. We formulate the drug-reaction relationship problem as a continuous optimization problem and … Read more
Multi-level production planning problems in which multiple items compete for the same resources frequently occur in practice, yet remain daunting in their difficulty to solve. In this paper we propose a heuristic framework that can generate high quality feasible solutions quickly for various kinds of lot-sizing problems. In addition, unlike many other heuristics, it generates … Read more
Continuous GRASP (C-GRASP) is a stochastic local search metaheuristic for finding cost-efficient solutions to continuous global optimization problems subject to box constraints (Hirsch et al., 2006). Like a greedy randomized adaptive search procedure (GRASP), a C-GRASP is a multi-start procedure where a starting solution for local improvement is constructed in a greedy randomized fashion. In … Read more
We present an algorithm for finding a feasible solution to a convex mixed integer nonlinear program. This algorithm, called Feasibility Pump, alternates between solving nonlinear programs and mixed integer linear programs. We also discuss how the algorithm can be iterated so as to improve the first solution it finds, as well as its integration within … Read more
Local optimizations introduced to obtain improved tours for Traveling Salesman Problem have a great impact on the final solution. That is way we introduce a new ant system algorithm with a new local updating pheromone rule, and the tours are improved using k-opt techniques. The tests use different parameters, in order to obtain solutions close … Read more
We address a multi-item capacitated lot-sizing problem with setup times that arises in real-world production planning contexts. Demand cannot be backlogged, but can be totally or partially lost. Safety stock is an objective to reach rather than an industrial constraint to respect. The problem is NP-hard. A mixed integer mathematical formulation is presented. We propose … Read more
We propose a Greedy Randomized Adaptive Search Procedure (GRASP) for solving continuous global optimization problems subject to box constraints. The method was tested on benchmark functions and the computational results show that our approach was able to find, in a few seconds, optimal solutions for all tested functions despite not using any gradient information about … Read more
In the DIMACS benchmark suite for the maximum clique problem, the best known solution for test C2000.9 is a 78 nodes clique; optimality is not proved. We present a 79 nodes clique emerged during the testing of a heuristic algorithm. Article Download View Short communication: a larger clique for a DIMACS test