scholarly journals REPLENISHMENT POLICY FOR A PROCESSING SYSTEM WITH STOCHASTIC CONSTRAINTS, DISCOUNT AND IMPERFECT ITEMS

2020 ◽  
Vol 51 (1) ◽  
pp. 37-42
Author(s):  
S. Momeni ◽  
B. Afshar-Nadjafi
Keyword(s):  
Model Performance ◽  
Processing System ◽  
Mixed Integer ◽  
Optimal Order ◽  
Multiple Products ◽  
Imperfect Items ◽  
Replenishment Policy ◽  
Total Inventory ◽  
Order Quantities ◽  
Stochastic Constraints

In this paper, a processing system with multiple products, single-vendor and single-buyer is considered to maximize the inventory system’s profit. In order to be more suit for real-world applications, this model contains five stochastic constraints including backordering cost, space, ordering, procurement, and available budget. It is assumed that orders are subjected to quantity discount and also imperfect goods are permitted. The price of the perfect and imperfect goods are assumed to be different. The imperfect goods are assumed to be returned to the system for rework process. The objective is to find the optimal order quantities of products such that the total inventory profit to be maximized while satisfying all the constraints. The problem is formulated as a mixed integer nonlinear programming problem. Two algorithms, based on GA and GRASP are developed to solve the resulting model. Performance of the algorithms are analyzed based on 45 numerical examples with different sizes.

scholarly journals Proposal of Product-Replenishment Policy Determination on Multi-Source Problems to Minimize Over Stock in DC PT. XYZ Area Bandung Using Mixed-Integer Programming Method

2019 ◽  
Vol 3 (01) ◽  
pp. 21-27
Author(s):  
Saskia Dyah ◽  
Rio Aurachman ◽  
Budi Santosa
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Method ◽  
Mixed Integer ◽  
Main Function ◽  
Order Quantity ◽  
Distribution Centers ◽  
Replenishment Policy ◽  
Holding Cost ◽  
Total Inventory

XYZ is one of the companies engaging in fast moving consumer goods (FMCG) sector and produce soft drinks as its main product. In supporting the product distribution to its customers, PT XYZ has several administrative offices and distribution centers (DC) which spread across each region. The DC has main function as the warehouse which has storage activity before the products are distributed. One of the DC is located in Bandung, West Java. DC Bandung itself received product shipments from three factories, such as Cibitung, Cakung and Tambun. Related to the product shipment, DC Bandung has not determined the replenishment policy, and this condition results over stock at some periods, due to the unscheduled delivery time and undetermined product quantity. This condition gives a big impact to the total inventory cost that has to be borne by DC Bandung. This research was conducted to give the proposal of product replenishment policy using mathematical model with mixed-integer programming method as one of the linear programming types, which aimed to minimize over stock and total holding cost in DC Bandung with several constraints. Mathematical modeling is involved in this research as an approximation to the real replenishment system in the DC. The results of application of the proposed method are in the form of analytical solution, such as order quantity, and reorder point of each product that will give an impact to the total unit inventory and the total holding cost in the DC. The results calculation of replenishment policy provide savings on total inventory costs as much as IDR 23,800,981.20 Keywords—Mixed-Integer Programming, Order Quantity, Over Stock, Replenishment Policy.

Coordination Policies for Multi-Echelon Multi-Product Inventory Systems

2011 ◽  
pp. 153-163
Author(s):  
Fidel Torres ◽  
Gonzalo Mejía
Keyword(s):  
Mathematical Model ◽  
Inventory Systems ◽  
Optimal Order ◽  
Distribution Centers ◽  
Operational Costs ◽  
Production Distribution ◽  
Replenishment Policy ◽  
Order Quantities ◽  
Product Inventory ◽  
Coordination And Collaboration

The effective coordination is a key element in the success of many cooperative supply chains. All production, distribution and supply must be adequately synchronized in order to satisfy the customer needs and at the same time optimizing the operational costs. This paper presents a multi-product, multi-echelon inventory system which comprises one manufacturer, a number of distribution centers and a number of retailers which are dependent of such distribution centers. The coordination and collaboration is achieved through a carefully designed replenishment policy. The near-optimal order quantities for each of the supply chain agents are calculated with a mathematical model in which the integrality constraints are relaxed. A number of instances were generated and tested. The results show the validity of the proposed approach.

Coordination Policies for Multi-Echelon Multi-Product Inventory Systems

2012 ◽  
pp. 1239-1249
Author(s):  
Fidel Torres ◽  
Gonzalo Mejía
Keyword(s):  
Mathematical Model ◽  
Inventory Systems ◽  
Optimal Order ◽  
Distribution Centers ◽  
Operational Costs ◽  
Production Distribution ◽  
Replenishment Policy ◽  
Order Quantities ◽  
Product Inventory ◽  
Coordination And Collaboration

The effective coordination is a key element in the success of many cooperative supply chains. All production, distribution and supply must be adequately synchronized in order to satisfy the customer needs and at the same time optimizing the operational costs. This paper presents a multi-product, multi-echelon inventory system which comprises one manufacturer, a number of distribution centers and a number of retailers which are dependent of such distribution centers. The coordination and collaboration is achieved through a carefully designed replenishment policy. The near-optimal order quantities for each of the supply chain agents are calculated with a mathematical model in which the integrality constraints are relaxed. A number of instances were generated and tested. The results show the validity of the proposed approach.

scholarly journals Proposed Determination of Product-Replenishment Policy on Multi-Source Problems to Minimize Over Stock in DC PT. XYZ Area Bandung With Mixed-Integer Programming Method

2019 ◽  
Vol 3 (01) ◽  
pp. 50
Author(s):  
Saskia Dyah Choirida ◽  
Rio Aurachman ◽  
Budi Santosa
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Product Distribution ◽  
Programming Method ◽  
Mixed Integer ◽  
Main Function ◽  
Distribution Centers ◽  
Replenishment Policy ◽  
Holding Cost ◽  
Total Inventory

PT. XYZ is one of the companies which engages in fast moving consumer goods (FMCG) sector and has soft drinks as its main product. In supporting the product distribution to its customers, PT XYZ has several administrative offices and distribution centers (DC) which spread across each region. The DC has main function as the warehouse which has storage activity before the products are distributed. One of the DC is located in Bandung, West Java. DC Bandung itself received product shipments from three factories, such as Cibitung, Cakung and Tambun. Related to the product shipment, DC Bandung has not determined the replenishment policy, and this condition results over stock at some periods, due to the unscheduled delivery time and undetermined product quantity. This condition gives a big impact to the total inventory cost that has to be borne by DC Bandung. This research was conducted to give the proposal of product replenishment policy with mixed-integer programming method, as one of the linear programming types, which aimed to minimize over stock and total holding cost in DC Bandung. Mathematical model is also involved in this research as an approximation to the real replenishment system in the DC. The results of application of the proposed method are in the form of analytical solution, such as order quantity, and reorder point of each product that will give an impact to the total unit inventory and the total holding cost in the DC. The results calculation of replenishment policy provide savings on total inventory costs as much as IDR 23,800,981.20

Dynamic supplier selection approach for mining equipment company

2019 ◽  
Vol 14 (1) ◽  
pp. 77-105 ◽  
Author(s):  
Md. Tanweer Ahmad ◽  
Sandeep Mondal
Keyword(s):  
Sensitivity Analysis ◽  
Supplier Selection ◽  
Business Environment ◽  
Spare Parts ◽  
Mixed Integer ◽  
Optimal Order ◽  
Mining Equipment ◽  
Order Allocation ◽  
Managerial Implication ◽  
Content Type

PurposeThis paper aims to address the supplier selection (SS) problem under dynamic business environments to optimize the procurement cost of spare-parts in the context of a mining equipment company (MEC). Practically, involved parameters’ value does not remain constant as planning periods due to fluctuation in the demand and their market dynamics. Therefore, dynamicity in the parameter is considered as an important factor when a company forms a responsive chain through most eligible suppliers with respect to planning periods. This area of study may be considered for their complexities to the approaches toward order-allocations with bi-products of unused and repair spare-parts.Design/methodology/approachAn integrated methodology of analytic hierarchy process (AHP) and mixed-integer non-linear programming (MILP) is implemented in the two stages during each planning periods. In the first stage, AHP is used to obtain the relative weights with respect to each spare-parts of each criterion and based on that, the ranking is evaluated in accordance with case considered. And in the second stage, MILP is formulated to find the allocations of each spare-part with two distinct approaches through Model-1 and Model-2 separately. Moreover, Model-1 and Model-2 are outlined based on the ranking and efficient parameters-value under cost, limited capacities, quality level and delay lead time respectively.FindingsThe ranking and their optimal order-allocation of potential suppliers are obtained during consecutive planning periods for both unused and repair spare-parts. Subsequently, sensitivity analysis is conducted to deduce the key nuggets with the comparison of Model-1 and Model-2 in the changing of capacity, demand and cost per spare-parts. From this analysis, it is found that suppliers who have optimal parameter settings would be better for order-allocations than ranking during the changing planning period.Practical implicationsThis paper points out the situation-specific approach for SS problem for a mining industry which often faces disruptive supplying environments. The managerial implication between ranking and parameters are highlighted through Model-1 and Model-2 by sensitivity analysis.Originality/valueIt provides useful directions for managers who are involved in the procurement of spare-parts in the mining environment. For this, suppliers are selected for order-allocation by using Model-1 and Model-2 in the dynamic business environment. The solvability of the model is presented using LINGO 17. Furthermore, the case company selected in this study can be extended to other sectors.

scholarly journals A Clonal Selection Optimization System for Multiparty Secure Computing

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Minyu Shi ◽  
Yongting Zhang ◽  
Huanhuan Wang ◽  
Junfeng Hu ◽  
Xiang Wu
Keyword(s):  
Deep Learning ◽  
Large Scale ◽  
Differential Privacy ◽  
Clonal Selection ◽  
Smart Cities ◽  
Model Performance ◽  
Processing System ◽  
Optimization System ◽  
Learning Scheme ◽  
Training Efficiency

The innovation of the deep learning modeling scheme plays an important role in promoting the research of complex problems handled with artificial intelligence in smart cities and the development of the next generation of information technology. With the widespread use of smart interactive devices and systems, the exponential growth of data volume and the complex modeling requirements increase the difficulty of deep learning modeling, and the classical centralized deep learning modeling scheme has encountered bottlenecks in the improvement of model performance and the diversification of smart application scenarios. The parallel processing system in deep learning links the virtual information space with the physical world, although the distributed deep learning research has become a crucial concern with its unique advantages in training efficiency, and improving the availability of trained models and preventing privacy disclosure are still the main challenges faced by related research. To address these above issues in distributed deep learning, this research developed a clonal selective optimization system based on the federated learning framework for the model training process involving large-scale data. This system adopts the heuristic clonal selective strategy in local model optimization and optimizes the effect of federated training. First of all, this process enhances the adaptability and robustness of the federated learning scheme and improves the modeling performance and training efficiency. Furthermore, this research attempts to improve the privacy security defense capability of the federated learning scheme for big data through differential privacy preprocessing. The simulation results show that the proposed clonal selection optimization system based on federated learning has significant optimization ability on model basic performance, stability, and privacy.

scholarly journals An Optimal Order Quantity Of Spare Parts To Minimize Total Inventory Cost Using Periodic Review Approach (R,s,s) Method In PT. XYZ Bandung

2017 ◽  
Vol 1 (02) ◽  
Author(s):  
Feviana Betsi Purba ◽  
Luciana Andrawina ◽  
Murni Dwi Astuti
Keyword(s):  
Spare Part ◽  
Spare Parts ◽  
Optimal Order ◽  
Periodic Review ◽  
Order Quantity ◽  
Inventory Cost ◽  
Inventory Policy ◽  
Total Saving ◽  
Manufacturing Company ◽  
Total Inventory

The availability of spare parts is very crucial thing for manufacturing company in order to support the continuity of production activities. PT XYZ is a manufacturing company which produces thread into fabric. In this case, inventory control of spare part is not properly managed. Inventory position of spare parts in warehouse is always more than inventory policy of the company itself or called overstock which causes total inventory cost is always high. Company only consider on the order fulfillment of spare parts to prevent downtime on the machine that increase performance of production. Hence, order quantity of spare parts is always excessive or not optimal. In this research, global inventory policy conducted in order to minimize total inventory cost is periodic review approach (R, s, S) method. This inventory policy will be calculated using power approximation and obtained total saving cost of holding cost by 31 % while total saving cost of order cost decreased by 7 %. Overall, total inventory cost minimized by 7 % or equal to Rp138.902.742.

scholarly journals A Green Demand-Responsive Airport Shuttle Service Problem with Time-Varying Speeds

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Ming Wei ◽  
Binbin Jing ◽  
Jian Yin ◽  
Yang Zang
Keyword(s):  
Time Windows ◽  
Operating Cost ◽  
Model Performance ◽  
Path Selection ◽  
Mixed Integer ◽  
Time Varying ◽  
Alternative Fuel Vehicles ◽  
Nsga Ii ◽  
The Difference ◽  
On The Road

This study proposes a multiobjective mixed integer linear programming (MOMILP) model for a demand-responsive airport shuttle service. The approach aims to assign a set of alternative fuel vehicles (AFVs) located at different depots to visit each demand point within the specified time and transport all of them to the airport. The proposed model effectively captures the interactions between path selection and environmental protection. Moreover, users with flexible pick-up time windows, the time-varying speed of vehicles on the road network, and the limited fuel for the route duration are also fully considered in this model. The work aims at simultaneously minimizing the operating cost, vehicle fuel consumption, and CO2 emissions. Since this task is an NP-hard problem, a heuristic-based nondominated sorting genetic algorithm (NSGA-II) is also presented to find Pareto optimal solutions in a reasonable amount of time. Finally, a real-world example is provided to illustrate the proposed methodology. The results demonstrate that the model not only selects an optimal depot for each AFV but also determines its route and timetable plan. A sensitivity analysis is also given to assess the effect of early/late arrival penalty weights and the number of AFVs on the model performance, and the difference in quality between the proposed and traditional models is compared.

scholarly journals Combining retrosynthesis and mixed-integer optimization for minimizing the chemical inventory needed to realize a WHO essential medicines list

2020 ◽  
Vol 5 (2) ◽  
pp. 367-376
Author(s):  
Hanyu Gao ◽  
Connor W. Coley ◽  
Thomas J. Struble ◽  
Linyan Li ◽  
Yujie Qian ◽  
...  
Keyword(s):  
Essential Medicines ◽  
Mixed Integer ◽  
Integer Optimization ◽  
Mixed Integer Optimization ◽  
Essential Medicines List ◽  
Multiple Products ◽  
On Demand

Retrosynthetic pathways suggestions are optimized to minimize the number of unique chemicals required to synthesize multiple products as would be useful for on-demand manufacturing.

Supplies from developing countries: Optimal order quantities under loss risks

Omega ◽  
2008 ◽  
Vol 36 (1) ◽  
pp. 122-130 ◽  
Author(s):  
Jayavel Sounderpandian ◽  
Sameer Prasad ◽  
Manu Madan
Keyword(s):  
Developing Countries ◽  
Optimal Order ◽  
Order Quantities
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