نتایج جستجو برای: hybrid meta heuristic

تعداد نتایج: 401324  

Esmaeil Mehdizadeh Fariborz Jolai Masoud Jenabi Mohammad Aliabadi

Many authors have examined lot sizing, scheduling and sequence of multi-product flow shops, but most of them have assumed that set up times are independent of sequence. Whereas dependence of set up times to sequence is more common in practice. Hence, in this paper, we examine the discussed problem with hypothesis of dependence of set up times to sequence and cyclic schedule policy in basic peri...

This paper presents a robust hybrid improved dolphin echolocation and ant colony optimization algorithm (IDEACO) for optimization of truss structures with discrete sizing variables. The dolphin echolocation (DE) is inspired by the navigation and hunting behavior of dolphins. An improved version of dolphin echolocation (IDE), as the main engine, is proposed and uses the positive attributes of an...

Journal: :journal of optimization in industrial engineering 2013
javad rezaeian hany seidgar morteza kiani

this paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. the objective is to minimize the weighted sum of makespan and maximum tardiness. three meta-heuristic methods based on genetic algorithm (ga), imperialist competitive algorithm (ica) and a hybrid approach of ga a...

In most real world application and problems, a homogeneous product is carried from an origin to a destination by using different transportation modes (e.g., road, air, rail and water). This paper investigates a fixed charge transportation problem (FCTP), in which there are different routes with different capacities between suppliers and customers. To solve such a NP-hard problem, four meta-heur...

2017
K. Sheibani

We describe a hybrid meta-heuristic algorithm for combinatorial optimization problems with a specific reference to the travelling salesman problem (TSP). The method is a combination of a genetic algorithm (GA) and greedy randomized adaptive search procedure (GRASP). A new adaptive fuzzy a greedy search operator is developed for this hybrid method. Computational experiments using a wide range of...

This paper presents a new mathematical model for a hybrid flow shop scheduling problem with multiprocessor tasks in which sequence dependent set up times and preemption are considered. The objective is to minimize the weighted sum of makespan and maximum tardiness. Three meta-heuristic methods based on genetic algorithm (GA), imperialist competitive algorithm (ICA) and a hybrid approach of GA a...

ژورنال: علوم آب و خاک 2022

Accurate prediction of pore water pressure in the body of earth dams during construction with accurate methods is one of the most important components in managing the stability of earth dams. The main objective of this research is to develop hybrid models based on fuzzy neural inference systems and meta-heuristic optimization algorithms. In this regard, the fuzzy neural inference system and opt...

This paper develops Order Acceptance for an Integrated Production-Distribution Problem in which Batch Delivery is implemented. The aim of this problem is to coordinate: (1) rejecting some of the orders (2) production scheduling of the accepted orders and (3) batch delivery to maximize Total Net Profit. A Mixed Integer Programming is proposed for the problem. In addition, a hybrid meta-heuristic...

Assigning facilities to locations is one of the important problems, which significantly is influence in transportation cost reduction. In this study, we solve quadratic assignment problem (QAP), using a meta-heuristic algorithm with deterministic tasks and equality in facilities and location number. It should be noted that any facility must be assign to only one location. In this paper, first o...

2013
Rashmi G. Dukhi

Feature selection is vital in the field of pattern classification due to accuracy and processing time considerations.The selection of proper features is of greater importance when the initial feature set is considerably large. Text classification is a typical example of this situation, where the size of the initial feature set may reach to hundreds or even thousands. There are numerous research...

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