scholarly journals Optimal Production and Inventory Policy in a Multiproduct Bakery Unit

Processes ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 101
Author(s):  
Belmiro P. M. Duarte ◽  
André M. M. Gonçalves ◽  
Lino O. Santos
Keyword(s):  
Inventory Control ◽  
Efficient Solutions ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Setup Cost ◽  
Model Framework ◽  
Optimal Production ◽  
Inventory Policy ◽  
Multiple Products ◽  
The Cost

The problem of finding optimal production and inventory policies is crucial for companies of the food industry, especially those processing multiple products. Since companies are required to adopt the most efficient solutions to prosper, the operation at these optimal conditions can have an extensive impact on profit, resource allocation and product quality. We address the problem of finding the optimal production and inventory policy in a multiproduct bakery unit for two contexts: (i) deterministic consumption without inventory control; and (ii) stochastic consumption combined with delayed inventory control. A formulation is proposed for each of these two setups. The restrictions considered in the model framework are related to workforce availability, and the cost structure includes four components: (i) production cost; (ii) inventory cost; (iii) setup cost; and (iv) the cost due to the degradation of perceived quality. The problem is formulated as a Mixed Integer Linear Programming one and solved with a branch and cut algorithm-based solver. The formulation is applied to a real bakery unit producing a mix of eight products. Distinct demand and inventory lower levels are used for building scenarios to test both models and characterize the economic performance of the multiproduct bakery unit.

Multi-objective and multi-period optimization of a regional timber supply network with uncertainty

2020 ◽  
Vol 50 (2) ◽  
pp. 203-214 ◽  
Author(s):  
Cheng Chen ◽  
Jianbang Gan ◽  
Zhengxiong Zhang ◽  
Rongzu Qiu
Keyword(s):  
Demand Uncertainty ◽  
Ghg Emissions ◽  
Fuzzy Linear Programming ◽  
Mixed Integer ◽  
Generic Model ◽  
Distribution Centers ◽  
Model Framework ◽  
Timber Supply ◽  
Supply Networks ◽  
The Cost

To assess the impacts of uncertainty and environmental objectives on the configuration of timber supply networks, we develop a generic multi-period, mixed-integer fuzzy linear programming model with demand uncertainty and two objectives of minimizing total transportation cost and greenhouse gas (GHG) emissions. We then use the triangular fuzzy number method to define the uncertain demands and convert the model into its equivalent auxiliary crisp counterpart. To derive Pareto solutions more efficiently, we propose the nondominated sorting genetic algorithm (NSGA-II) to solve the model. Finally, we apply the model framework and solution method to a real-world case of regional timber supply in Fujian, China, to demonstrate their applicability. The simulation results of the model show that trade-offs exist between total cost and GHG emissions and that the proper selection of the number and locations of distribution centers can help reduce both the cost and GHG emissions. Demand uncertainty and supply fluctuations across different time periods can increase the cost and GHG emissions. Our empirical results provide useful insights into the design and management of regional timber supply networks, and our generic model is applicable to the analysis of regional supply networks of other products or materials besides timber.

scholarly journals Unit commitment based reliability analysis with contingency constraint

2019 ◽  
Vol 16 (1) ◽  
pp. 74
Author(s):  
Raheema Syed ◽  
P. Srinivasa Varma ◽  
R. B. R Prakash ◽  
Ch. Rami Reddy
Keyword(s):  
Power Plants ◽  
Benders Decomposition ◽  
Unit Commitment ◽  
Reliability Assessment ◽  
Branch And Cut ◽  
Mixed Integer ◽  
Unit Commitment Problem ◽  
Commitment Problem ◽  
Model Reliability ◽  
The Cost

<span lang="EN-IN">Unit commitment state’s the strategic choice to be prepared in order to define which of the accessible power plants should be taken into account to supply power. It permits utilities to reduce generation price of power. In this paper, the unit commitment problem is elucidated by taking N-1-1 contingency as a foremost constraint. The standard N-1-1 contingency takes the loss of sequential two components in the network having intervening interval for network modifications in the middle of two losses. The crucial objective to carry out contingency constrictions is to make certain that the operations of power system are adequately strong to unexpected losses of the components of the network. The optimal scheduling/allocation of the generating units is resolved by taking into account the N-1-1 criterion of contingency. By considering the N-1-1 criterion of contingency, the problem results to give an optimised model which is a linear model of mixed integer form. The linear program of mixed integer is a technique of an operational assessment in which restriction is imposed on few variables to be integers. Primarily benders decomposition was considered but for the improvement of results, the algorithm of branch and cut is presented. IEEE 30 bus system is taken into consideration and widespread analysis is accomplished to associate performance of the system under N-1-1 criterion contingency. The computational outcomes determine the value for taking into concern the intervening interval for the adjustments of the system with respect to the cost and robustness of the system. Later to the above model reliability assessment is proposed to calculate the Loss Of Load Expected (LOLE). This model is solved using MATLAB/MATPOWER software.</span>

Optimal Production-Inventory Policy for a Periodic-Review Energy Buy-Back System over an Infinite Planning Horizon

2020 ◽  
Vol 37 (02) ◽  
pp. 2050001
Author(s):  
Hong-Qiao Chen ◽  
Xiao-Song Ding ◽  
Ji-Hong Zhang ◽  
Hua-Yi Li
Keyword(s):  
Planning Horizon ◽  
Periodic Review ◽  
Setup Cost ◽  
Optimal Production ◽  
Inventory Policy ◽  
Discounted Cost ◽  
Production Inventory ◽  
Inventory Control Model ◽  
Buy Back ◽  
Infinite Planning Horizon

This paper studies a periodic-review production-inventory control model under an energy buy-back program over an infinite planning horizon, in which a fixed setup cost and compensation levels corresponding to various market states are involved. The objective is to identify the manufacturer’s optimal production-inventory policy that can minimize his total discounted cost or long-run average cost. By using Veinott’s conditions, it is shown that such a state dependent optimal policy is of either an [Formula: see text], or partly an [Formula: see text] type.

scholarly journals Design and Adoption of Low-Cost Point-of-Care Diagnostic Devices: Syrian Case

Micromachines ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 882
Author(s):  
M. Munzer Alseed ◽  
Hamzah Syed ◽  
Mehmet Cengiz Onbasli ◽  
Ali K. Yetisen ◽  
Savas Tasoglu
Keyword(s):  
Civil Wars ◽  
Healthcare Workers ◽  
New Technologies ◽  
Point Of Care ◽  
Low Cost ◽  
Healthcare Services ◽  
Efficient Solutions ◽  
Humanitarian Crises ◽  
Technology Experience ◽  
The Cost

Civil wars produce immense humanitarian crises, causing millions of individuals to seek refuge in other countries. The rate of disease prevalence has inclined among the refugees, increasing the cost of healthcare. Complex medical conditions and high numbers of patients at healthcare centers overwhelm the healthcare system and delay diagnosis and treatment. Point-of-care (PoC) testing can provide efficient solutions to high equipment cost, late diagnosis, and low accessibility of healthcare services. However, the development of PoC devices in developing countries is challenged by several barriers. Such PoC devices may not be adopted due to prejudices about new technologies and the need for special training to use some of these devices. Here, we investigated the concerns of end users regarding PoC devices by surveying healthcare workers and doctors. The tendency to adopt PoC device changes is based on demographic factors such as work sector, education, and technology experience. The most apparent concern about PoC devices was issues regarding low accuracy, according to the surveyed clinicians.

scholarly journals An Optimized Mathematical Model for Items Supplies Planning of a Logistic System

2016 ◽  
Vol 10 (10) ◽  
pp. 133
Author(s):  
Mohammad Ali Nasiri Khalili ◽  
Mostafa Kafaei Razavi ◽  
Morteza Kafaee Razavi
Keyword(s):  
Mathematical Model ◽  
Mixed Integer ◽  
Logistics System ◽  
Proposed Model ◽  
Multiple Objective Decision Making ◽  
System Requirements ◽  
Purchasing Logistics ◽  
The Cost ◽  
The Mathematical Model ◽  
First Time

Items supplies planning of a logistic system is one of the major issue in operations research. In this article the aim is to determine how much of each item per month from each supplier logistics system requirements must be provided. To do this, a novel multi objective mixed integer programming mathematical model is offered for the first time. Since in logistics system, delivery on time is very important, the first objective is minimization of time in delivery on time costs (including lack and maintenance costs) and the cost of purchasing logistics system. The second objective function is minimization of the transportation supplier costs. Solving the mathematical model shows how to use the Multiple Objective Decision Making (MODM) can provide the ensuring policy and transportation logistics needed items. This model is solved with CPLEX and computational results show the effectiveness of the proposed model.

Enterprise Inventory Control Based on Supply Chain Management

2012 ◽  
Vol 472-475 ◽  
pp. 3273-3276
Author(s):  
Qing Ying Zhang ◽  
Ying Chi ◽  
Yu Liu ◽  
Qian Shi
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Inventory Control ◽  
Control Strategies ◽  
Minimum Cost ◽  
Chain Management ◽  
Main Target ◽  
The Cost

The main target of supply chain management is to control inventory of each node enterprise effectively with the minimum cost. In this paper, the control strategies and methods of inventory based on supply chain management are put forward, which are significant for saving the cost of supply chain and improving the overall benefits of the whole chain.

scholarly journals Lagrangian Relaxation for an Inventory Location Problem with Periodic Inventory Control and Stochastic Capacity Constraints

2018 ◽  
Vol 2018 ◽  
pp. 1-27 ◽  
Author(s):  
Claudio Araya-Sassi ◽  
Pablo A. Miranda ◽  
Germán Paredes-Belmar
Keyword(s):  
Inventory Control ◽  
Lagrangian Relaxation ◽  
Location Problem ◽  
Subgradient Method ◽  
Capacity Constraints ◽  
Mixed Integer ◽  
Total System ◽  
Periodic Review ◽  
Decomposition Approach ◽  
Stochastic Capacity

We studied a joint inventory location problem assuming a periodic review for inventory control. A single plant supplies a set of products to multiple warehouses and they serve a set of customers or retailers. The problem consists in determining which potential warehouses should be opened and which retailers should be served by the selected warehouses as well as their reorder points and order sizes while minimizing the total costs. The problem is a Mixed Integer Nonlinear Programming (MINLP) model, which is nonconvex in terms of stochastic capacity constraints and the objective function. We propose a solution approach based on a Lagrangian relaxation and the subgradient method. The decomposition approach considers the relaxation of different sets of constraints, including customer assignment, warehouse demand, and variance constraints. In addition, we develop a Lagrangian heuristic to determine a feasible solution at each iteration of the subgradient method. The proposed Lagrangian relaxation algorithm provides low duality gaps and near-optimal solutions with competitive computational times. It also shows significant impacts of the selected inventory control policy into total system costs and network configuration, when it is compared with different review period values.

scholarly journals Cost-Effective Resource Sharing in an Internet of Vehicles-Employed Mobile Edge Computing Environment

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 594 ◽  
Author(s):  
Tri Nguyen ◽  
Tien-Dung Nguyen ◽  
Van Nguyen ◽  
Xuan-Qui Pham ◽  
Eui-Nam Huh
Keyword(s):  
Video Streaming ◽  
Resource Sharing ◽  
Vehicular Network ◽  
Edge Computing ◽  
Mixed Integer ◽  
Mobile Users ◽  
Vehicle Speed ◽  
Mobile Edge Computing ◽  
Internet Of Vehicles ◽  
The Cost

By bringing the computation and storage resources close proximity to the mobile network edge, mobile edge computing (MEC) is a key enabling technology for satisfying the Internet of Vehicles (IoV) infotainment applications’ requirements, e.g., video streaming service (VSA). However, the explosive growth of mobile video traffic brings challenges for video streaming providers (VSPs). One known issue is that a huge traffic burden on the vehicular network leads to increasing VSP costs for providing VSA to mobile users (i.e., autonomous vehicles). To address this issue, an efficient resource sharing scheme between underutilized vehicular resources is a promising solution to reduce the cost of serving VSA in the vehicular network. Therefore, we propose a new VSA model based on the lower cost of obtaining data from vehicles and then minimize the VSP’s cost. By using existing data resources from nearby vehicles, our proposal can reduce the cost of providing video service to mobile users. Specifically, we formulate our problem as mixed integer nonlinear programming (MINP) in order to calculate the total payment of the VSP. In addition, we introduce an incentive mechanism to encourage users to rent its resources. Our solution represents a strategy to optimize the VSP serving cost under the quality of service (QoS) requirements. Simulation results demonstrate that our proposed mechanism is possible to achieve up to 21% and 11% cost-savings in terms of the request arrival rate and vehicle speed, in comparison with other existing schemes, respectively.

Fuzzy Economic Production Quantity Model for Weibull Deteriorating Items with Ramp Type of Demand

2011 ◽  
Vol 2 (3) ◽  
pp. 55-90 ◽  
Author(s):  
R. Uthayakumar ◽  
M. Valliathal
Keyword(s):  
Deteriorating Items ◽  
Quantity Discounts ◽  
Setup Cost ◽  
Economic Production Quantity ◽  
Deterministic Demand ◽  
Economic Production ◽  
Holding Cost ◽  
Production Quantity ◽  
Delay In Payments ◽  
The Cost

This paper discusses an Economic Production Quantity model for Weibull deteriorating items over an infinite time horizon under fuzzy environment. Fuzziness is introduced by allowing the cost components such as setup cost, production cost, holding cost, shortage cost and opportunity cost due to lost sales to certain extent. Triangular fuzzy numbers are used to represent the mentioned costs. Optimum policies of the described models under fuzzy costs are derived. The proposed model can be extended in several ways. For instance, the deterministic demand function to stochastic fluctuating demand patterns could be considered. The model could also be generalized to allow for quantity discounts, as well as permissible delay in payments.

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