in this study, we discuss the capacitated facility location-allocation problem with uncertain parameters in which the uncertainty is characterized by given finite numbers of scenarios. in this model, the objective function minimizes the total expected costs of transportation and opening facilities subject to the robustness constraint. to tackle the problem efficiently and effectively, an effici...

Mean Field Genetic Algorithm (MGA) is a hybrid algorithm of Mean Field Annealing (MFA) and Simulated annealing-like Genetic Algorithm (SGA). It combines benefit of rapid convergence property of MFA and effective genetic operations of SGA. This paper presents an approach for building a multi-classifier system in a MGA-based inductive learning environment. Multiple base classifiers are combined t...

We study errors of quantum annealing and simulated annealing to highlight better performance of quantum annealing over simulated annealing. Quantum annealing and simulated annealing perform optimization through a quantum adiabatic evolution and a quasi-static evolution respectively. In both methods, dynamics across a phase transition plays a crucial role. The Kibble-Zurek mechanism is known as ...

the markowitz issue of optimization can’t be solved by precise mathematical methods such as second order schematization, when real world condition and limitations are considered. on the other hand, most managers prefer to manage a small portfolio of available assets in place of a huge portfolio. it can be analogized to cardinal constrains, that is, constrains related to minimum and maximum curr...

Pairwise testing, which requires that every combination of valid values of each pair of system factors be covered by at lease one test case, plays an important role in software testing since many faults are caused by unexpected 2-way interactions among system factors. Although meta-heuristic strategies like simulated annealing can generally discover smaller pairwise test suite, they may cost mo...

This paper explores the use of the meta-heuristic search algorithm Simulated Annealing for solving a minimum cost network synthesis problem. This problem is a common one in the design of telecommunication networks. The formulation we use models a number of practical problems with hop-limit, degree and capacity constraints. Emphasis is placed on a new approach that uses a knapsack polytope to se...

Capabilities of enhanced simulated-annealing-based algorithms in solving process planning problems in reconfigurable manufacturing are investigated. The algorithms are enhanced by combining variants of the simulated annealing technique with other algorithm concepts such as (i) knowledge exploitation and (ii) parallelism. Four configurations of simulated annealing algorithms are devised and enga...

in this paper, a stochastic multi-depot multi-objective vehicle routing problem (vrp) is studied. based on observations in real-world problems, we develop an aspect of the problem, such as stochastic availability of routes. to solve the problem in this situation, a two-objective mathematical model is developed, in which the related objective functions are: (1) minimizing transportation costs an...

School timetabling is way of distributing resources such as teachers and classrooms over a fixed period of time. This task can be difficult and very time-consuming. If the process of generating timetables is automated with the help of algorithms then this can help save both time and money for the educational institute. In this thesis a general timetable is presented along with a set of constrai...