In the current competitive conditions, all the manufacturers’ efforts are focused on increasing the customer satisfaction as well as reducing the production and delivery costs; thus, there is an increasing concentration on the structure and principles of supply chain (SC). Accordingly, the present research investigated simultaneous optimization of the total costs of a chain and customer satisfa...

The multiple traveling salesman problem (MTSP) involves scheduling m > 1 salesmen to visit a set of n > m nodes so that each node is visited exactly once. The objective is to minimize the total distance traveled by all the salesmen. The MTSP is an example of combinatorial optimization problems, and has a multiplicity of applications, mostly in the areas of routing and scheduling. In this paper,...

Controlled tabular adjustment is an SDL methodology based on a mixed integer linear programming model. We develop new hybrid heuristics and new metaheuristic learning approaches for solving this model, and examine their performance. Our new approaches are based on partitioning the problem into its discrete and continuous components, and first creating a hybrid that reduces the number of binary ...

The metaheuristics are approximation methods which deal with difficult optimization problems. The Work that we present in this paper has primarily as an objective the adaptation and the implementation of two advanced metaheuristics which are the Memetic Algorithms (MA) and the Electromagnetism Metaheuristic (EM) applied in the production systems of Hybrid Flow Shop (HFS) type for the problem of...

this paper studies the multi-stage supply chain system (msscm) controlled by the kanban mechanism. in the kanban system, decision making is based on the number of kanbans as well as batch sizes. a kanban mechanism is employed to assist in linking different production processes in a supply chain system in order to implement the scope of just-in-time (jit) philosophy. for a msscm, a mixed-integer...

Hybrid metaheuristics have received considerable interest in recent years. Since several years ago, a wide variety of hybrid approaches have been proposed in the literature including the new GA-EDA approach. We have design and implemented an extension to this GA-EDA approach, based on statistical significance tests. This approach had allowed us to make an study of the balance of diversification...

This paper considers open-shop scheduling with no intermediate buffer to minimize total tardiness. This problem occurs in many production settings, in the plastic molding, chemical, and food processing industries. The paper mathematically formulates the problem by a mixed integer linear program. The problem can be optimally solved by the model. The paper also develops a novel metaheuristic base...

This paper proposes a modified sine cosine algorithm (MSCA) for discrete sizing optimization of truss structures. The original sine cosine algorithm (SCA) is a population-based metaheuristic that fluctuates the search agents about the best solution based on sine and cosine functions. The efficiency of the original SCA in solving standard optimization problems of well-known mathematical function...