Routing problems aim to find the lowest cost and shortest route among many possible routes. The Travelling Salesman Problem (TSP) is the most popular routing problem in which a seller must go to all cities of the map through the shortest route and return to the first point. In general, several factors can be considered for simultaneous motion on a map, which is called the Vehicle Routing Problem (VRP). With math programming techniques, you can only get the optimal solution for small size problems. These problems belong to NP-hard problems.

Using automatic scheduling is one of the most important tools for improving the quality of project management. Scheduling can be long term or daily. From a small office to a large company, all depend on correct scheduling. Many efforts are being made to generate new scheduling methods by considering various conditions and assumptions. Schedule-related problems are part of larger NP-hard problems called optimization problems. There are two important features in these problems: first, constraints that indicate the needs each solution should meet. For example, a particular task should not begin before the completion of some other tasks. Second, the objective function which examines the quality of a solution. The quality of a solution is related to the makespan. Resource assignment problems are a simpler form of scheduling problems in which each resource can be assigned to any activity, but each activity has only one resource at a time. There are, of course, more complex resource assignment problems in practice. These complexities can include limited resources, multiple assignments, partial assignments, and so on. Getting the optimal solution for the above problems is very time consuming and also impossible for large size problems Using nature-inspired optimization algorithms, we can obtain a near-optimal solutions in a reasonable timeframe. Search methods like genetic algorithm (GA), particle swarm optimization (PSO) algorithm, artificial bee colony optimization algorithm (ABC), etc. can be used.

In this Special Issue, we invite researchers to optimize the problems using nature-inspired optimization methods. It is expected that by combining new methods and using innovative functions better, near-optimal solutions will be found for the problems. Original research and review articles are welcome.

Potential topics include but are not limited to the following:

• Application of approximate algorithms to solve NP-hard routing problems
• Combine search methods to optimize TSP
• Using evolutionary methods to solve VRP
• Using swarm intelligence algorithms to solve VRP
• Solve resource allocation problems in Internet of things domain
• Optimizing resource allocation in cloud computing
• Heuristic methods to solve the open shop problem
• Using optimization algorithms in the flow shop problem
• Optimization of the flow shop problem using search methods
• Using heuristic functions and optimization algorithms to solve the job shop problem