the cuckoo search algorithm is a recently developedmeta-heuristic optimization algorithm, which is suitable forsolving optimization problems. to enhance the accuracy andconvergence rate of this algorithm, an improved cuckoo searchalgorithm is proposed in this paper. normally, the parametersof the cuckoo search are kept constant. this may lead todecreasing the efficiency of the algorithm. to cop...

The vehicle routing problem (VRP), a well-known combinatorial optimization problem, holds a central place in logistics management. Many meta-heuristic approaches like Simulated Annealing (SA), Genetic Algorithms (GA), Tabu Search (TS), and Ant Colony Optimization (ACO) have been proposed to solve VRP. Ant Algorithm is a distributed meta-heuristic approach that has been applied to various combin...

the capacitated vehicle routing problem (cvrp) is a well-known combinatorial optimization problem that holds a central place in logistics management. the vehicle routing is an applied task in the industrial transportation for which an optimal solution will lead us to better services, save more time and ultimately increase in customer satisfaction. this problem is classified into np-hard problem...

in this study, a bi-objective model for integrated planning of production-distribution in a multi-level supply chain network with multiple product types and multi time periods is presented. the supply chain network including manufacturers, distribution centers, retailers and final customers is proposed. the proposed model minimizes the total supply chain costs and transforming time of products ...

one of the most important and valuable goal of software development life cycle is software cost estimation or sce. during the recent years, sce has attracted the attention of researchers due to huge amount of software project requests. there have been proposed so many models using heuristic and meta-heuristic algorithms to do machine learning process for sce. cocomo81 is one of the most popular...

In this chapter, we review a few important concepts from Grid computing related to scheduling problems and their resolution using heuristic and meta-heuristic approaches. Scheduling problems are at the heart of any Grid-like computational system. Different types of scheduling based on different criteria, such as static vs. dynamic environment, multi-objectivity, adaptivity, etc., are identified...

In this paper we survey computational models for Grid scheduling problems and their resolution using heuristic and meta-heuristic approaches. Scheduling problems are at the heart of any Grid-like computational system. Different types of scheduling based on different criteria, such as static versus dynamic environment,multi-objectivity, adaptivity, etc., are identified. Then, heuristic andmeta-h...

Flow shop scheduling of jobs has always been a popular problem that has found solutions in the number of heuristic and meta-heuristic techniques. In this manuscript, two-machine flow shop scheduling problem has been investigated while optimizing makespan and idle time of machines. Uncertainties in the processing time and set up times of jobs involved are also taken into consideration in the for...

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...