Evolutionary algorithms are general iterative algorithms for combinatorial optimization. The term evolutionary algorithm is used to refer to any probabilistic algorithm whose design is inspired by evolutionary mechanisms found in biological species. These algorithms have been found to be very effective and robust in solving numerous problems from a wide range of application domains. In this pap...

Capacitated vehicle routing problems are widely studied combinatorial optimization problems, and branch-and-cut-and-price algorithms can solve instances harder than ever before. These models, however, neglect that demands volumes often not known with precision when planning the routes, thus incentivizing decision makers to significantly overestimate for avoiding coping infeasible routes. A robu...

assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. in this study, we solve quadratic assignment problem (qap), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. it should be noted that any facility must be assign to only one location. in this paper, first o...

Genetic algorithms are a population-based Meta heuristics. They have been successfully applied to many optimization problems. However, premature convergence is an inherent characteristic of such classical genetic algorithms that makes them incapable of searching numerous solutions of the problem domain. A memetic algorithm is an extension of the traditional genetic algorithm. It uses a local se...

Many traditional algorithms for solving combinatorial optimization problems involve using hand-crafted heuristics that sequentially construct a solution. Such are designed by domain experts and may often be suboptimal due to the hard nature of problems. Reinforcement learning (RL) proposes good alternative automate search these training an agent in supervised or self-supervised manner. In this ...

In the age of Big Data the problem of storing huge volume of data in a minimum storage space by utilizing available resources properly is an open problem and an important research aspect in recent days. This problem has a close relationship with the famous classical NP-Hard combinatorial optimization problem namely the “Bin Packing Problem” where bins represent available storage space and the p...