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The Multi-objective Vehicle Routing Problem (MoVRP) is an important problem in the logistics distribution management, whose two objective functions are to minimize the global transportation cost and to maximize the average customer satisfaction. The mixed integer programming model of MoVRP is proposed in this paper. And a Hybrid Genetic Algorithm based on Human-Computer Interaction (HGAHCI) is presented...
In this paper, advanced planning and scheduling (APS) in which each customer order has an absolute due date and outsourcing is available in a manufacturing supply chain is addressed. An integer programming model is presented to solve the APS problem. The objective is to minimize the makespan of each customer order while satisfying the due date constraints. The proposed model considers the integration...
This paper researches the optimization of injection strategies of polymer flooding in oil recovery. An optimal control problem (OCP) of a distributed parameter system (DPS) is formulated, in which the functional of performance index is profit maximum and the governing equations are the fluid equations in porous media. The control variables are chosen as the polymer concentrations and the slug size...
In this paper, the mixed-integer nonlinear programming model is established for hybrid flow-shop scheduling problem (HFSP), with the minimum of energy consumption as the objective function. Aiming at the characteristic of this problem and the shortcomings of simple genetic algorithm, a hybrid genetic algorithm (Memetic) is presented. To validate the preciseness of the model and the availability of...
According to the complexity and risk of the reverse logistics, the main objective of this paper is to propose a multistage methodology for designing a reverse logistics network from the risk management perspective. Firstly, we applied fuzzy DEA model to assess the candidate reverse logistics suppliers based on the risk management. Furthermore, we founded a mixed integer programming model by considering...
Numerous real-world problems relating to flow-shop scheduling are characterized by combinatorially explosive alternatives as well as multiple conflicting objectives and are denoted as multiobjective combinatorial optimization problems. The problem of multiobjective optimization with setup times in flow shop is considered in this study. The objective function of the problem is minimization of the weighted...
Production scheduling has been recognized as common but challenging combinatorial problems. Because of their complexity, recent research has turned to genetic algorithms to address such problems. Although genetic algorithms have been proven to facilitate the entire space search, they lack in fine-tuning capability for obtaining the global optimum. Therefore, in this study a hybrid genetic algorithm...
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