scholarly journals Design of a Distribution Network Using Primal-Dual Decomposition

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
J. A. Marmolejo ◽  
R. Rodríguez ◽  
O. Cruz-Mejia ◽  
J. Saucedo
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Distribution Network ◽  
Mixed Integer ◽  
Direct Solution ◽  
Distribution Centers ◽  
Dual Decomposition ◽  
Primal Dual ◽  
Cross Decomposition ◽  
Primal And Dual

A method to solve the design of a distribution network for bottled drinks company is introduced. The distribution network proposed includes three stages: manufacturing centers, consolidation centers using cross-docking, and distribution centers. The problem is formulated using a mixed-integer programming model in the deterministic and single period contexts. Because the problem considers several elements in each stage, a direct solution is very complicated. For medium-to-large instances the problem falls into large scale. Based on that, a primal-dual decomposition known as cross decomposition is proposed in this paper. This approach allows exploring simultaneously the primal and dual subproblems of the original problem. A comparison of the direct solution with a mixed-integer lineal programming solver versus the cross decomposition is shown for several randomly generated instances. Results show the good performance of the method proposed.

scholarly journals Supply chain optimization with variable demand by considering financial criteria and scenarios

2017 ◽  
Vol 26 (44) ◽  
pp. 21 ◽  
Author(s):  
John Willmer Escobar
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Net Present Value ◽  
Programming Model ◽  
Supply Chain Design ◽  
Mixed Integer ◽  
Supply Network ◽  
Distribution Centers ◽  
Supply Chain Optimization ◽  
Starting Point

This paper contemplates the supply chain design problem of a large-scale company by considering the maximization of the Net Present Value. In particular, the variability of the demand for each type of product at each customer zone has been estimated. As starting point, this paper considers an established supply chain for which the main problem is to determine the decisions regarding expansion of distribution centers. The problem is solved by using a mixed-integer linear programming model, which optimizes the different demand scenarios. The proposed methodology uses a scheme of optimization based on the generation of multiple demand scenarios of the supply network. The model is based on a real case taken from a multinational food company, which supplies to the Colombian and some international markets. The obtained results were compared with the equivalent present costs minimization scheme of the supply network, and showed the importance and efficiency of the proposed approach as an alternative for the supply chain design with stochastic parameters.

scholarly journals A Propose Model Optimal Supply Chain Distribution Network for Farmer Industrial

2020 ◽  
Vol 3 (2) ◽  
pp. 43-53
Author(s):  
Ammar Salamh Mujali Al-Rawahna ◽  
Anas Yahya Bader Al Hadid
Keyword(s):  
Supply Chain ◽  
Network Flows ◽  
Programming Model ◽  
Cost Minimization ◽  
Distribution Network ◽  
Distribution Networks ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Supply Chain System ◽  
External Interface

A supply chain should be operated in the most efficient way in a highly competitive environment, with the goals of cost minimization, shipment delays, inventories and expenditures, and distribution maximization, gain, return on investment, level of customer support, and efficiency. The development of supply-chain distribution networks is therefore an extremely complex task, due to the large physical production and distribution network flows, the uncertainties associated with external interface customers and suppliers as well as the non-linear dynamics linked to internal information flows. This study aims to address a problem in domestic distribution in a supply chain system that includes manufacturers, distribution centers and consumer zones to determine the optimum configuration of the network. We propose a mixed integer linear programming model to solve the problem.

scholarly journals A Decomposition Strategy for Optimal Design of a Soda Company Distribution System

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
J. A. Marmolejo ◽  
I. Soria ◽  
H. A. Perez
Keyword(s):  
Distribution System ◽  
Large Scale ◽  
Programming Model ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Computational Time ◽  
Fixed Costs ◽  
Distribution Centers ◽  
Cross Docking

This work presents a distribution problem of products of a soda bottling company. Commodities are produced at several plants with limited capacity and the demand of distribution centers is satisfied by shipping via cross-docking warehouses. The decomposition strategy is proposed to determine which warehouse needs to be opened to consolidate the demand and by which warehouse each distribution center is served exclusively. The objective is minimizing fixed costs and total transportation costs. The model presented is a mixed-integer programming model with binary variables for which we propose a decomposition strategy based on Benders algorithm. Numerical results show that the proposed strategy can provide the optimal solution of several instances. A large-scale case study based on a realistic company situation is analyzed. Solutions obtained by the proposed method are compared with the solution of full scale problem in order to determine the quality bound and computational time.

scholarly journals A stochastic location and allocation model for critical items to response large-scale emergencies: A case of Turkey

2016 ◽  
Vol 7 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Erkan Celik ◽  
Nezir Aydin ◽  
Alev Taskin Gumus
Keyword(s):  
Large Scale ◽  
Programming Model ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Allocation Model ◽  
Proposed Model ◽  
Stochastic Mixed Integer Programming ◽  
Stochastic Location ◽  
Relief Organizations

This paper aims to decide on the number of facilities and their locations, procurement for pre and post-disaster, and allocation to mitigate the effects of large-scale emergencies. A two-stage stochastic mixed integer programming model is proposed that combines facility location- prepositioning, decisions on pre-stocking levels for emergency supplies, and allocation of located distribution centers (DCs) to affected locations and distribution of those supplies to several demand locations after large-scale emergencies with uncertainty in demand. Also, the use of the model is demonstrated through a case study for prepositioning of supplies in probable large-scale emergencies in the eastern and southeastern Anatolian sides of Turkey. The results provide a framework for relief organizations to determine the location and number of DCs in different settings, by using the proposed model considering the main parameters, as; capacity of facilities, probability of being affected for each demand points, severity of events, maximum distance between a demand point and distribution center. 

scholarly journals Resource Allocation for Energy Efficient User Association in User-Centric Ultra-Dense Networks Integrating NOMA and Beamforming

2020 ◽  
Author(s):  
Long Zhang ◽  
Guobin Zhang ◽  
Xiaofang Zhao ◽  
Yali Li ◽  
Chuntian Huang ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Large Scale ◽  
Mixed Integer ◽  
Joint Optimization ◽  
User Association ◽  
Dual Decomposition ◽  
Dense Networks ◽  
Wireless Backhaul ◽  
User Centric

A coupling of wireless access via non-orthogonal multiple access and wireless backhaul via beamforming is a promising way for downlink user-centric ultra-dense networks (UDNs) to improve system performance. However, ultra-dense deployment of radio access points in macrocell and user-centric view of network design in UDNs raise important concerns about resource allocation and user association, among which notably is energy efficiency (EE) balance. To overcome this challenge, we develop a framework to investigate the resource allocation problem for energy efficient user association in such a scenario. The joint optimization framework aiming at the system EE maximization is formulated as a large-scale non-convex mixed-integer nonlinear programming problem, which is NP-hard to solve directly with lower complexity. Alternatively, taking advantages of sum-of-ratios decoupling and successive convex approximation methods, we transform the original problem into a series of convex optimization subproblems. Then we solve each subproblem through Lagrangian dual decomposition, and design an iterative algorithm in a distributed way that realizes the joint optimization of power allocation, sub-channel assignment, and user association simultaneously. Simulation results demonstrate the effectiveness and practicality of our proposed framework, which achieves the rapid convergence speed and ensures a beneficial improvement of system-wide EE.<br>

scholarly journals An Improved Decomposition Approach and its Computational Technique for Analyzing Primal-Dual Relationship in LP & LFP Problems

2014 ◽  
Vol 33 ◽  
pp. 65-75
Author(s):  
HK Das ◽  
M Babul Hasan
Keyword(s):  
Computational Technique ◽  
Dual Decomposition ◽  
Linear Fractional Programming ◽  
Decomposition Approach ◽  
Dual Approach ◽  
Numerical Examples ◽  
Primal Dual ◽  
Primal And Dual ◽  
Relationship Of ◽  
The Relationship

In this paper, we study the methodology of primal dual solutions in Linear Programming (LP) & Linear Fractional Programming (LFP) problems. A comparative study is also made on different duals of LP & LFP. We then develop an improved decomposition approach for showing the relationship of primal and dual approach of LP & LFP problems by giving algorithm. Numerical examples are given to demonstrate our method. A computer programming code is also developed for showing primal and dual decomposition approach of LP & LFP with proper instructions using AMPL. Finally, we have drawn a conclusion stating the privilege of our method of computation. GANIT J. Bangladesh Math. Soc. Vol. 33 (2013) 65-75 DOI: http://dx.doi.org/10.3329/ganit.v33i0.17660

scholarly journals Multidepot Heterogeneous Vehicle Routing Problem for a Variety of Hazardous Materials with Risk Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Bochen Wang ◽  
Qiyuan Qian ◽  
Zheyi Tan ◽  
Peng Zhang ◽  
Aizhi Wu ◽  
...  
Keyword(s):  
Risk Analysis ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Programming Model ◽  
Hazardous Materials ◽  
Mixed Integer ◽  
Small Scale ◽  
Routing Problem ◽  
Heterogeneous Vehicle Routing Problem

This study investigates a multidepot heterogeneous vehicle routing problem for a variety of hazardous materials with risk analysis, which is a practical problem in the actual industrial field. The objective of the problem is to design a series of routes that minimize the total cost composed of transportation cost, risk cost, and overtime work cost. Comprehensive consideration of factors such as transportation costs, multiple depots, heterogeneous vehicles, risks, and multiple accident scenarios is involved in our study. The problem is defined as a mixed integer programming model. A bidirectional tuning heuristic algorithm and particle swarm optimization algorithm are developed to solve the problem of different scales of instances. Computational results are competitive such that our algorithm can obtain effective results in small-scale instances and show great efficiency in large-scale instances with 70 customers, 30 vehicles, and 3 types of hazardous materials.

scholarly journals Scheduling Just-in-Time Transport Vehicles to Feed Parts for Mixed Model Assembly Lines

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Yunfang Peng ◽  
Tian Zeng ◽  
Yajuan Han ◽  
Beixin Xia
Keyword(s):  
Large Scale ◽  
Assembly Line ◽  
Mixed Model ◽  
Programming Model ◽  
Primary Objective ◽  
Mixed Integer ◽  
Inventory Level ◽  
Just In Time ◽  
Time Model ◽  
Delivery Strategy

In order to solve the problem of vehicle scheduling to feed parts at automobile assembly line, this study proposes a just-in-time delivery method combined with the mode of material supermarket. A mixed integer linear programming model with the primary objective of using the least number of tow trains is constructed by considering capacity of vehicle and inventory levels of line. On the basis of the minimum number of tow trains, the schedule of each tour is reasonably planned to minimize inventory of assembly line, which is the secondary objective of the part supply problem. Additionally, a heuristic algorithm which can obtain a satisfactory solution in a short time is designed to solve large-scale problems after considering continuity and complexity of modern automobile production. Furthermore, some cases are analyzed and compared with the widely used periodic delivery strategy, and the feasibility of just-in-time model and algorithm is verified. The results reveal that just-in-time delivery strategy has more advantages in reducing inventory level than periodic delivery strategy.

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