The traveling salesman problem (TSP) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. The TSP is probably the most famous and extensively studied problem in the field of combinatorial optimization. Because this problem is an NP-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

This paper considers the problem of scheduling hybrid flowshops with machine availability constraints (MAC) to minimize makespan. The paper deals with a specific case of MAC caused by preventive maintenance (PM) operations. Contrary to previous papers considering fixed or/and conservative policies, we explore a case in which PM activities might be postponed or expedited while necessary. Regardi...

This study is devoted to discrete sizing optimization of truss structures employing an efficient discrete evolutionary meta-heuristic algorithm which uses the Newton gradient-based method as its updating scheme and it is named here as Newton Meta-heuristic Algorithm (NMA). In order to enable the NMA population-based meta-heuristic to effectively explore the discrete design space, a term contain...

The traveling salesman problem (TSP) is the problem of finding the shortest tour through all the nodes that a salesman has to visit. The TSP is probably the most famous and extensively studied problem in the field of combinatorial optimization. Because this problem is an NP-hard problem, practical large-scale instances cannot be solved by exact algorithms within acceptable computational times. ...

The vehicle routing problem with the capacity constraints was considered in this paper. It is quite difficult to achieve an optimal solution with traditional optimization methods by reason of the high computational complexity for large-scale problems. Consequently, new heuristic or metaheuristic approaches have been developed to solve this problem. In this paper, we constructed a new heuristic ...

In this paper, a new hybrid metaheuristic algorithm based on the scatter search approach is developed to solve the well-known resource-constrained project scheduling problem. This algorithm combines two solutions from scatter search to build a set of precedence feasible activity lists and select some of them as children for the new population. We use the idea presented in the iN forward/backwar...

In this paper a new metaheuristic solution is designed to solve the travelling salesperson problem with hotel selection (TSPHS). The applied solution approach is based on the V flight formation of migrating birds. Different numerical analysis confirms that it is efficient enough for solving the problem in a reasonable computational time. To check the efficiency and suitability of the solution a...

Mesh partitioning is an important problem that has extensive applications in many areas. Multilevel algorithms are a successful class of optimization techniques which addresses the mesh partitioning problem. In this paper we present an enhancement of the technique that uses nature inspired metaheuristic to achieve higher quality partitions. We apply and study a multilevel ant-colony (MACO) opti...

Emissions resulted from transportation activities may lead to dangerous effects on the whole environment and human health. According to sustainability principles, in recent years researchers attempt to consider the environmental burden of logistics activities in traditional logistics problems such as vehicle routing problems (VRPs). The pollution-routing problem (PRP) is an extension of the VRP...

Optimum design of steel frames is a complicated process because the designer has to consider a large number of nonlinear constraints which are imposed by steel design codes while also dealing with discrete design variables. Obtaining the optimum solution to discrete programming problems was never easy until the emergence of metaheuristic techniques. The firefly algorithm, one of the recent meta...