this paper addresses the vehicle routing problem with delivery time cost. this problem aims to find a set of routes of minimal total costs including the travelling cost and delivery time cost, starting and ending at the depot, in such a way that each customer is visited by one vehicle given the capacity of the vehicle to satisfy a specific demand. in this research, a hybrid metaheuristic approa...

We proposed a population-based metaheuristic called the spy algorithm for solving optimization problems and evaluated its performance. The design of our ensures benefit exploration exploitation as well cooperative non-cooperative searches in each iteration. compared with genetic algorithm, improved harmony search, particle swarm on set non-convex functions that focus accuracy, ability detecting...

the exponential growth of the flow of goods and passengers, fragility of certain products and the need for the optimization of transport costs impose on carriers to use more and more multimodal transport. in addition, the need for intermodal transport policy has been strongly driven by environmental concerns and to benefit from the combination of different modes of transport to cope with the in...

Metaheuristic algorithms are used to solve NP-hard optimization problems. These algorithms have two main components, i.e. exploration and exploitation, and try to strike a balance between exploration and exploitation to achieve the best possible near-optimal solution. The bat algorithm is one of the metaheuristic algorithms with poor exploration and exploitation. In this paper, exploration and ...

the urban waste collection is one of the major municipal activities that involves large expenditures and difficult operational problems. also, waste collection and disposal have high expenses such as investment cost (i.e. vehicles fleet) and high operational cost (i.e. fuel, maintenance). in fact, making slight improvements in this issue lead to a huge saving in municipal consumption. some inci...

Increasing nature-inspired metaheuristic algorithms are applied to solving the real-world optimization problems, as they have some advantages over the classical methods of numerical optimization. This paper has proposed a new nature-inspired metaheuristic called Whale Swarm Algorithm for function optimization, which is inspired by the whales’ behavior of communicating with each other via ultras...

This paper proposes a mixed integer programming model to solve a non-identical parallel machine (NIPM) scheduling with sequence-dependent set-up times and human resiliency engineering. The presented mathematical model is formulated to consider human factors including Learning, Teamwork and Awareness. Moreover, processing time of jobs are assumed to be non-deterministic and dependent to their st...

We present a novel application of the Artificial Bee Colony algorithm to solve the non-unicost Set Covering Problem. The Artificial Bee Colony algorithm is a recent Swarm Metaheuristic technique based on the intelligent foraging behavior of honey bees. We present a 2-level metaheuristic approach where an Artificial Bee Colony Algorithm acts as a low-level metaheuristic and its paremeters are se...