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In this paper, a single machine batch process scheduling problem (SBPSP) integrating batching decision is investigated. The integration problem of batching and scheduling is to allocate the demands from different customer orders to sets of batches and schedule these batches such that the total weighted tardiness costs and the total set-up costs are minimized. This problem is formulated as a mixed-integer...
Sku assignment is an essential problem for the design and operation of Automated Picking System (APS), which is mainly composed of Horizontal Dispenser (HD) and A-frame. The challenge is to develop an effective measurement to evaluate the sku and the efficient assignment procedure in practice. Based on fluid model, the optimal number of channels allotted to each sku to minimize the total restocking...
Tasks scheduling problem is a key factor for a distributed system in order to achieve better efficiency. The problem of tasks scheduling in a distributed system can be stated as allocating tasks to processor of each computer. The objective of this problem is minimizing Makespan and communication cost while maximizing CPU utilization. Scheduling problem is known as NP-complete. Hence, many genetic...
Aiming at the stock problems faced by brand traders such as out-of-stock and overstock, this thesis has analyzed what leads to the stock problems of fashionable products and puts forward a demand forecast model of three stages with the help of an operation model of fashionable products' supply chain. A stock control model and an inspiring formula that fits those brand traders' fashionable products...
n jobs, each job i with a minimum processing time pi and a weight wi, have to be processed on a batching machine with capacity B. Minimization of total weighted completion time for single batching machine is a classical scheduling problem. Dijkstra's algorithm, the method to find the shortest path in a graph, is used to partition the jobs into batches. And it can get the optimal batches for a certain...
This paper aims to establish a dynamic vessel fleet planning model in uncertain circumstance, which offers the shipping companies the appropriate development strategy. Based on the characteristics of the shipping market, we consider the market volatility faced by the shipping companies on the strategies of the fleet planning. Firstly, we establish a forecast model to predict the future shipping demand...
This paper considers the multi-processor scheduling problem with unequal release dates to minimize total completion times. This problem is proved to be NP-hard in the strong sense. Traditional forward algorithms base on the heuristic rule SPT (shortest processing time first) and ERD (earliest release date first) for the problem are analyzed. A backward algorithm BA is proposed to avoid the limitation...
Production scheduling is critical for manufacturing system. Dispatching rules are usually applied dynamically to schedule the job in the dynamic job-shop. The paper presents an adaptive iterative scheduling algorithm that operates dynamically to schedule the job in the dynamic job-shop. In order to get adaptive behavior, the reinforcement learning system is done with the phased Q-learning by defining...
A new classified scheduling method based on the controlled Petri net and GASA was proposed to the job-shop scheduling problem (JSP) with multiple disturbances constrained by machines, workers. Firstly, a Petri net with controller is modeled, it not only has the modeling capability of a traditional Petri net, but also it can depict system characteristics, such as equipment maintenance, different types...
The cold rolling production scheduling problem is an extremely difficult process, so it is quite difficult to achieve an optimal solution with traditional optimization methods. Based on rolling feature of continuous tandem cold rolling mill, such as multi-variable, strong coupling, non-linear, this paper presents a particle swarm optimization (PSO) algorithm schedule optimization procedure for tandem...
After the analysis of movement of subway under moving block system, the problem of operation adjustment is studied. The model of the problem is constructed. The objective are decreasing the total delay time and increasing the absorption to passengers of the successive trains. The technology of agent and multi-agent is adopted in the construction of train agent and the design of operation adjustment...
A new stable artificial immune self-tuning PID control scheme is proposed. The model is adapted by artificial immune clustering algorithm to learn plant dynamic change, while the PID control parameters are adapted by the Lyapunov method to minimize a cost function. Therefore, the model output is guaranteed to converge to the desired trajectory asymptotically, and the plant output also tracks the desired...
The restraint combination optimization question of the cold rolling production scheduling is typical NP-hard problem, which included the width, thickness, degree of hardness jump, product stock and tows the penalty of the rolling tube blank. To establish minimum value model of the cold rolling production batch scheduling problem based on TSP, and then proposed Improved Ant Group Algorithm which combined...
The single batch-processing machine scheduling problem with re-entrance to minimize total weighted completion time is considered, where the capacity of the machine is infinite and there are different processing types in the same machine. This problem can be transformed into a model with parallel chains precedence constraint. A polynomial time heuristic algorithm for the problem is given. Experimentation...
In this paper, we design a nonlinear model for hot rolling process optimization which takes minimizing energy consumption and getting good shape as the objective function. Differential evolution (DE) algorithm is a useful algorithm for solving nonlinear optimization problem. The conventional DE algorithm is easy to get into local optimization, so we propose an improved DE algorithm by adjusting the...
There is a major problem with traditional artificial potential field method. It is the formation of local minima that can trap the robot before reaching its goal. To overcome the problem, this paper presents an improved potential field approach. It consists of two parts. The former, the improved attractive potential function, brings the minimum distance between the robot and the obstacle into consideration,...
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