‎This paper proposes a multi-supplier multi-product inventory model in which the suppliers have unlimited production capacity, allow delayed payment, and offer either an all-unit or incremental discount. The retailer can delay payment until after they have sold all the units of the purchased product. The retailer’s warehouse is limited, but the surplus can be stored in a rented warehouse at a...

this paper addresses the vehicle routing problem with delivery time cost. this problem aims to find a set of routes of minimal total costs including the travelling cost and delivery time cost, starting and ending at the depot, in such a way that each customer is visited by one vehicle given the capacity of the vehicle to satisfy a specific demand. in this research, a hybrid metaheuristic approa...

bilevel programming, a tool for modeling decentralized decision problems, consists of the objective of the leader at its first level and that of the follower at the second level. bilevel programming has been proved to be an np-hard problem. numerous algorithms have been developed for solving bilevel programming problems. these algorithms lack the required efficiency for solving a real problem. ...

Multi Objective Job Shop Scheduling Problem (MOJSP) is a problem for finding optimal operation sequences of some jobs according to more than one goal to achieve. The problem gets harder as its complexity increases. The development of optimization method has led many new methods to solve this problem. This paper offers Cross Entropy-Genetic Algorithm (CEGA) method to solve job shop scheduling pr...

In this paper, we propose sequential Monte Carlo simulated annealing (SMC-SA), a populationbased simulated annealing algorithm, for continuous global optimization. SMC-SA incorporates the sequential Monte Carlo method to track the converging sequence of Boltzmann distributions in simulated annealing, such that the empirical distribution will converge weakly to the uniform distribution on the se...

Genetic algorithm is a combinatorial optimization problem solving in the field of search algorithm, because of its versatility and robustness, it has been widely used in various fields of science. However, there are some defects in traditional genetic algorithm. for its shortcomings, this paper proposed an improved genetic algorithm for multi-objective Flexible JSP (job shop scheduling) problem...

A genetic algorithm implemented in Matlab is presented. Matlab is used for the following reasons: it provides many built in auxiliary functions useful for function optimization; it is completely portable; and it is eecient for numerical computations. The genetic algorithm toolbox developed is tested on a series of non-linear, multi-modal, non-convex test problems and compared with results using...

This paper presents a Simulated Annealing (SA) algorithm for solving the Environmental/Economic Dispatch Problem (EED). This problem is formulated as a multi-objective one with two competing functions, namely economic cost and emission functions, subject to different constraints. The inequality constraints considered are maximum and minimum limits of power generation while the equality constrai...

In this paper a new graph partitioning problem is introduced, the relaxed k-way graph partitioning problem. It is close to the k-way, also called multi-way, graph partitioning problem, but with relaxed imbalance constraints. This problem arises in the air traffic control area. A new graph partitioning method is presented, the Fusion Fission, which can be used to resolve the relaxed k-way graph ...

In this paper, a combination of simulated annealing (SA) and intelligent water drops (IWD) algorithm is used to solve the nonlinear/complex problem of simultaneous reconfiguration with optimal allocation (size and location) of wind turbine (WT) as a distributed generation (DG) and dynamic voltage restorer (DVR) as a distributed flexible AC transmission systems (DFACT) unit in a distribution sys...