This paper presents a multi-objective mathematical model which aims to optimize and harmonize supply chain reduce costs, improve quality, achieve competitive advantage position using meta-heuristic algorithms. The purpose of optimization in this field is increase quality customer satisfaction production time related prices. present research simultaneously optimized the multi-product multi-perio...

In this paper a multi-objective mathematical model has been used to optimize grinding parameters include workpiece speed, depth of cut and wheel speed which highly affect the final surface quality. The optimization problem consists three conflict objective functions subject wear production rate constraints. Exact methods can solve NLP in few seconds, therefore using Meta-heuristic algorithms pr...

The problem of the distribution of dairy products, which is classified as a combinatorial optimization problem, cannot be solved in polynomial time. In this paper, an algorithm based on Ant Colony Hybrid meta-heuristic system and Geographic Information System (GIS) was used to find a near-optimal solution to this problem. Using the former method, the nearest neighbor heuristic algorithm was use...

Multi-resolution approach to optimisation involving remodelling of objective function has great received interests lately. There are two different goals of remodelling for the objective function. First, the reduction of computational complexity of the objective functions in order to accelerate the searching process. Second, the removal of local optima in the objective functions to avoid prematu...

In this research, a bi-objective scheduling problem with controllable processing times on identical parallel machines is investigated. The direction of this paper is mainly motivated by the adoption of the just-in-time (JIT) philosophy on identical parallel machines in terms of bi-objective approach, where the job processing times are controllable. The aim of this study is to simultaneously min...

Ontology alignment is an essential and complex task to integrate heterogeneous ontology. The meta-heuristic algorithm has proven be effective method for ontology alignment. However, it only applies the inherent advantages of meta-heuristics rarely considers execution efficiency, especially multi-objective model. performance such optimization models mostly depends on well-distributed fast-conver...

Abstract In this paper, a new nature-inspire meta-heuristic algorithm called future search (FSA) is proposed for the first time to solve simultaneous optimal allocation of distribution generation (DG) and electric vehicle (EV) fleets considering techno-environmental aspects in operation control radial networks (RDN). By imitating human behavior getting fruitful life, FSA starts arbitrary search...

the capacitated clustering problem (ccp) is one of the most importantcombinational optimization problems that nowadays has many real applications inindustrial and service problems. in the ccp, a given n nodes with known demandsmust be partitioned into k distinct clusters in which each cluster is detailed by anode acting as a cluster center of this cluster. the objective is to minimize the sumof...

Exact optimization algorithms are not able to provide an appropriate solution in solving optimization problems with a high-dimensional search space. In these problems, the search space grows exponentially with the problem size therefore; exhaustive search is not practical. Also, classical approximate optimization methods like greedy-based algorithms make several assumptions to solve the problem...