Hybrid Metaheuristics Algorithms for Inventory Management Problems
نویسندگان
چکیده
The hybrid metaheuristics algorithms (HMHAs) have gained a considerable attention for their capability to solve difficult problems in different fields of science. This chapter introduces some applications of HMHAs in solving inventory theory problems. Three basic inventory problems, joint replenishment EOQ problem, newsboy problem, and stochastic review problem, in certain and uncertain environments such as stochastic, rough, and fuzzy environments with six different applications, are considered. Several HMHAs such as genetic algorithm (GA), simulated annealing (SA), particle swarm optimization (PSO), harmony search (HS), variable neighborhood search (VNS), and bees colony optimization (BCO) methods are used to solve the inventory problems. The proposed metaheuristics algorithms also are combined with fuzzy simulation, rough simulation, Pareto selecting and goal programming approaches. The computational performance of all of them, on solving these three optimization problems, is compared together. DOI: 10.4018/978-1-4666-2086-5.ch011
منابع مشابه
Modeling and scheduling no-idle hybrid flow shop problems
Although several papers have studied no-idle scheduling problems, they all focus on flow shops, assuming one processor at each working stage. But, companies commonly extend to hybrid flow shops by duplicating machines in parallel in stages. This paper considers the problem of scheduling no-idle hybrid flow shops. A mixed integer linear programming model is first developed to mathematically form...
متن کاملA multi-objective genetic algorithm (MOGA) for hybrid flow shop scheduling problem with assembly operation
Scheduling for a two-stage production system is one of the most common problems in production management. In this production system, a number of products are produced and each product is assembled from a set of parts. The parts are produced in the first stage that is a fabrication stage and then they are assembled in the second stage that usually is an assembly stage. In this article, the first...
متن کاملEmpirical Analysis of Two Different Metaheuristics for Real-World Vehicle Routing Problems
We present two hybrid Metaheuristics, a hybrid Iterated Local Search and a hybrid Simulated Annealing, for solving real-world extensions of the Vehicle Routing Problem with Time Windows. Both hybrid Metaheuristics are based on the same neighborhood generating operators and local search procedures. The initial solutions are obtained by the Coefficient Weighted Distance Time Heuristics with autom...
متن کاملNew Approaches in Metaheuristics to Solve the Truck Scheduling Problem in a Cross-docking Center
Nowadays, cross-docking is one of the main concepts in supply chain management in which products received to a distribution center by inbound trucks which are directly to lead into outbound trucks with a minimum handling and storage costs as the main cost of a cross-docking system. According to the literature, several metaheuristics and heuristics are attempted to solve this optimization model....
متن کاملDistributed Hybrid Metaheuristics for Optimization
A metaheuristic is an intelligent, iterative process that guides a search and can be applied towards optimization problems, such as the Traveling Salesman Problem. Two well studied techniques for solving optimization problems are Genetic Algorithms and Ant Colony Systems. However, each metaheuristic has different strengths and weaknesses. Genetic Algorithms are able to quickly find near optimal...
متن کامل