This paper presents a comprehensive multi-objective mixed integer mathematical programming model which considers cell formation and production planning problems simultaneously. This comprehensive model includes dynami...
详细信息
This paper presents a comprehensive multi-objective mixed integer mathematical programming model which considers cell formation and production planning problems simultaneously. This comprehensive model includes dynamic system reconfiguration, multi period production planning, operation sequence, alternative process plans for part types, machine and worker flexibility, duplicate machines, machine capacity, available time of workers and worker assignment. The aim of the proposed model is to minimize inter and intra-cell movement costs, machine and reconfiguration costs, setup costs, production planning costs (holding, backorder and subcontracting costs) and workers hiring, firing, training and salary costs, as well as minimizing summation of machines idle times as a second objective. Due to NP-hardness of the problem, a recent and efficient meta-heuristic algorithm namely multi-objective vibrationdampingoptimization (MOVDO) is designed for finding Pareto-optimal frontier. In order to check the efficiency of the developed algorithm, it is compared with two salient multi-objective genetic algorithms named NSGAII and NRGA. Finally, by generating some test problems in small and large scales and using some multi objective comparison metrics, the algorithms are compared and analyzed statistically. (C) 2016 Elsevier Ltd. All rights reserved.
In this article, designing an optimal path in two forms of point-to-point is investigated. In the first case, the optimal path planning and determination of the load-carrying capacity of a manipulator in a point-to-po...
详细信息
In this article, designing an optimal path in two forms of point-to-point is investigated. In the first case, the optimal path planning and determination of the load-carrying capacity of a manipulator in a point-to-point and open-loop case is studied. In the second case, the path-planning problem and maximum load-carrying capacity of manipulators are investigated in a closed-loop point-to-point case. Designing an optimal path in a point-to-point and open-loop case is studied using a vibration damping optimization algorithm. In order to design the controller in the closed-loop case, the game theory approach, which is a generalized form of nonlinear optimum control, is used. In this method, in addition to considering the dynamics of the manipulator, the dynamics of the driving system are also considered. Moreover, the method is able to investigate the effects of the disturbances introduced by the driving system. In the proposed method, the voltage of engines and system disturbances are considered as the players. The optimum strategy of players is calculated based on the Nash equilibrium strategy, and the optimum value of control inputs is determined using an iterative algorithm based on solving Riccati equations. The problem of designing a controller is proposed in the form of a differential game problem with zero sum. The results indicate that for a fixed-base two-link manipulator, the design of the controller based on a differential game made it possible to control the effect of system disturbances so that the load-carrying capacity experienced small changes compared to the desired case and without system disturbances resulting from the data obtained from point-to-point and open-loop cases.
The three problems of cell formation (CF), cellular scheduling, and cellular layout are closely interrelated in the design of cellular manufacturing systems (CMSs) and should, therefore, be considered in an integrated...
详细信息
The three problems of cell formation (CF), cellular scheduling, and cellular layout are closely interrelated in the design of cellular manufacturing systems (CMSs) and should, therefore, be considered in an integrated structure. This paper presents a mixed-integer programming (MIP) model to examine such concurrent design by considering many design attributes, such as the machine duplication, alternative processing routes, reentrant parts, and variable cell size. In the presented model, decisions including machine grouping, processing route selection, operation sequencing, and cell assignment into candidate locations are taken such that the total completion time is minimized. Since the problem in hand belongs to the NP-hard class, a vibrationdampingoptimization (VDO) algorithm is proposed to solve large-sized problems. In order to verify the efficiency of the proposed algorithm comparing to the CPLEX solver of the GAMS software and two other metaheuristic algorithms, namely a genetic algorithm (GA) and an ant lion optimizer (ALO) algorithm, several sample problems with different sizes and settings are implemented. The results demonstrate that the proposed algorithm can obtain better solutions in less computational time.
The purpose of this paper is to present a mixed-integer linear programming model for the scheduling problem in an open-shop manufacturing system involving reverse flows, where two job flows (direct and reverse) in two...
详细信息
The purpose of this paper is to present a mixed-integer linear programming model for the scheduling problem in an open-shop manufacturing system involving reverse flows, where two job flows (direct and reverse) in two opposite directions are processed on the same machines. The aim is to minimize the maximum completion time of all jobs on all machines (i.e., the makespan). A numerical example is presented and solved using the GAMS software (version 25.1.2) to validate the proposed mathematical model. As this problem is NP-hard, a vibrationdamping-based optimization (VDO) algorithm is proposed to solve large-scale problems in reasonable execution times. Besides, the Taguchi experimental design approach is employed to adjust and estimate the appropriate values of the VDO's parameters. Finally, the computational results of this algorithm are compared to the results obtained by a Simulated Annealing (SA), Cuckoo Search (CS), Ant Colony optimization (ACO), Harmony Search (HAS), Imperialist Competitive (ICA), and Bat algorithm (BA). The statistical comparison results on several randomly generated problems of different sizes using the Kruskal-Wallis test reveals the better performance of the VDO algorithm.
暂无评论