scholarly journals Modeling the Capacitated Multi-Level Lot-Sizing Problem under Time-Varying Environments and a Fix-and-Optimize Solution Approach

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 377 ◽  
Author(s):  
Meng You ◽  
Yiyong Xiao ◽  
Siyue Zhang ◽  
Shenghan Zhou ◽  
Pei Yang ◽  
...  
Keyword(s):  
Lot Sizing ◽  
Time Varying ◽  
Production Environment ◽  
Setup Costs ◽  
Lot Sizing Problem ◽  
Multi Level ◽  
Varying Environments ◽  
Time Varying Environment ◽  
Production Capacities ◽  
Varying Environment

In this study, we investigated the time-varying capacitated lot-sizing problem under a fast-changing production environment, where production factors such as the setup costs, inventory-holding costs, production capacities, or even material prices may be subject to continuous changes during the entire planning horizon. Traditional lot-sizing theorems and algorithms, which often assume a constant production environment, are no longer fit for this situation. We analyzed the time-varying environment of today’s agile enterprises and modeled the time-varying setup costs and the time-varying production capacities. Based on these, we presented two mixed-integer linear programming models for the time-varying capacitated single-level lot-sizing problem and the time-varying capacitated multi-level lot-sizing problem, respectively, with considerations on the impact of time-varying environments and dynamic capacity constraints. New properties of these models were analyzed on the solution’s feasibility and optimality. The solution quality was evaluated in terms of the entropy which indicated that the optimized production system had a lower value than that of the unoptimized one. A number of computational experiments were conducted on well-known benchmark problem instances using the AMPL/CPLEX to verify the proposed models and to test the computational effectiveness and efficiency, which showed that the new models are applicable to the time-varying environment. Two of the benchmark problems were updated with new best-known solutions in the experiments.

scholarly journals The Uncapacitatied Dynamic Single-Level Lot-Sizing Problem under a Time-Varying Environment and an Exact Solution Approach

2018 ◽  
Vol 10 (11) ◽  
pp. 3867
Author(s):  
Yiyong Xiao ◽  
Meng You ◽  
Xiaorong Zuo ◽  
Shenghan Zhou ◽  
Xing Pan
Keyword(s):  
Lot Sizing ◽  
Time Varying ◽  
Setup Cost ◽  
Single Level ◽  
Lot Sizing Problem ◽  
Dynamic Lot Sizing ◽  
Manufacturing Resources ◽  
Time Varying Environment ◽  
Forward Dynamic Programming ◽  
Varying Environment

The dynamic lot-sizing problem under a time-varying environment considers new features of the production system where factors such as production setup cost, unit inventory-holding cost, and unit price of manufacturing resources may vary in different periods over the whole planning horizon. Traditional lot-sizing theorems and algorithms are no longer fit for these situations as they had assumed constant environments. In our study, we investigated the dynamic lot-sizing problem with deteriorating production setup cost, a typical time-varying environment where the production setup is assumed to consume more preparing time and manufacturing resources as the production interval lasts longer. We proposed new lot-sizing models based on the traditional lot-sizing model considering the changing setup cost as a new constraint, called uncapacitatied dynamic single-level lot-sizing under a time-varying environment (UDSLLS-TVE for short). The UDSLLS-TVE problem has a more realistic significance and higher research value as it is closer to reality and has higher computational complexity as well. We proposed two mathematical programming models to describe UDSLLS_TVE with or without nonlinear components, respectively. Properties of the UDSLLS-TVE models were extensively analyzed and an exact algorithm based on forward dynamic programming (FDP) was proposed to solve this problem with a complexity of O (n2). Comparative experiments with the commercial MIP solver CPLEX on synthesized problem instances showed that the FDP algorithm is a global optimization algorithm and has a high computational efficiency.

MINIMALISASI BIAYA SIMPAN DAN BIAYA SETUP PADA MULTIPLE PRODUK: SIMULASI DENGAN CAPACITATED LOT SIZING PROBLEM

2019 ◽  
Vol 4 (2) ◽  
pp. 205-214
Author(s):  
Erika Fatma
Keyword(s):  
Production Cost ◽  
Lot Sizing ◽  
Setup Time ◽  
Production Costs ◽  
Total Production ◽  
Product Cycle ◽  
Lot Size ◽  
Setup Costs ◽  
Lot Sizing Problem ◽  
Capacitated Lot Sizing

Lot sizing problem in production planning aims to optimize production costs (processing, setup and holding cost) by fulfilling demand and resources capacity costraint. The Capacitated Lot sizing Problem (CLSP) model aims to balance the setup costs and inventory costs to obtain optimal total costs. The object of this study was a plastic component manufacturing company. This study use CLSP model, considering process costs, holding costs and setup costs, by calculating product cycle and setup time. The constraint of this model is the production time capacity and the storage capacity of the finished product. CLSP can reduce the total production cost by 4.05% and can reduce setup time by 46.75%.  Keyword: Lot size, CLSP, Total production cost.

scholarly journals Lot-sizing problem with several production centers

2005 ◽  
Vol 25 (3) ◽  
pp. 479-492 ◽  
Author(s):  
Franklina Maria Bragion de Toledo ◽  
André Luís Shiguemoto
Keyword(s):  
Dynamic Programming ◽  
Lot Sizing ◽  
Dynamic Programming Algorithm ◽  
Production Capacity ◽  
Efficient Implementation ◽  
Programming Algorithm ◽  
Future Research ◽  
Production Environment ◽  
Lot Sizing Problem ◽  
Forward Dynamic Programming

In this paper, a case study is carried out concerning the lot-sizing problem involving a single item production planning in several production centers that do not present capacity constraints. Demand can be met with backlogging or not. This problem results from simplifying practical problems, such as the material requirement planning (MRP) system and also lot-sizing problems with multiple items and limited production capacity. First we propose an efficient implementation of a forward dynamic programming algorithm for problems with one single production center. Although this does not reduce its complexity, it has shown to be rather effective, according to computational tests. Next, we studied the problem with a production environment composed of several production centers. For this problem two algorithms are implemented, the first one is an extension of the dynamic programming algorithm for one production center and the second one is an efficient implementation of the first algorithm. Their efficiency are shown by computational testing of the algorithms and proposals for future research are presented.

Minimum-Speed Motions

1991 ◽  
Vol 10 (3) ◽  
pp. 228-239 ◽  
Author(s):  
Boris Aronov ◽  
Steven Fortune ◽  
Gordon Wilfong
Keyword(s):  
Maximum Velocity ◽  
Initial Position ◽  
Linear Constraints ◽  
Initial Configuration ◽  
Full Description ◽  
Speed Limit ◽  
Time Varying ◽  
Moving Obstacles ◽  
Time Varying Environment ◽  
Varying Environment

We consider the problem of determining how fast an object must be capable of moving for it to be able to reach a given position at a given time while avoiding moving obstacles. The problem is to plan velocity profile along a given path so that collisions with moving obstacles crossing the path are avoided and the maximum velocity along the path is mini mized. Suppose the time-varying environment is fully speci fied, both in space and in time, by n linear constraints. An algorithm is presented that, given a full description of the environment and the initial configuration of the system (that is, initial position and starting time of the object), answers in O(log n) time queries of the form : "What is the lowest speed limit that the object can obey while still being able to reach the query configuration from the initial configuration without colliding with the obstacles?" The algorithm can also be used to compute a motion from the initial configuration to the query configuration that obeys the speed limit in O (n ) time. The algorithm requires O (n log n) preprocessing time and O (n) space.

Simulated On-Line Process Optimization of a Robotic Materials Handling System

1986 ◽  
Vol 108 (3) ◽  
pp. 285-291
Author(s):  
M. S. King ◽  
J. K. Blundell
Keyword(s):  
Process Optimization ◽  
Kinematic Model ◽  
Industrial Robots ◽  
Time Varying ◽  
Optimization Strategy ◽  
Materials Handling ◽  
On Line ◽  
Line Process ◽  
Time Varying Environment ◽  
Varying Environment

Industrial robots in use today lack the total ability to perceive and interact with their environment. This limitation is a major obstacle confronting robotic systems developers. This work outlines an on-line process optimization strategy which allows a robot to work within a time-varying environment. After developing the kinematic model of the robot and its relationship to its environment, the process optimization strategy is simulated. The performance of the system is measured by using an index of performance and comparing the simulation results against a series of non-optimized models. The results indicate that on-line process optimization strategy significantly increases the performance of a robotic system operating in a time-varying environment.

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