scholarly journals Integrated Production-Delivery Lot Sizing Model with Limited Production Capacity and Transportation Cost considering Overtime Work and Maintenance Time

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Renqian Zhang ◽  
Xuefang Sun
Keyword(s):  
Supply Chain ◽  
Numerical Experiment ◽  
Lot Sizing ◽  
Production Capacity ◽  
Transportation Cost ◽  
Solution Procedure ◽  
Sensitive Analysis ◽  
Integrated Production ◽  
Overtime Work ◽  
Maintenance Time

An extension of the integrated production-delivery lot sizing model with limited production capacity and transportation cost is investigated. We introduce the factor of overtime work into the model to improve the manufacturer’s production. In addition, when finishing a lot, the manufacturer has maintenance time to maintain and repair equipment for ensuring that the supply chain is operating continuously. By analyzing the integrated model, the solution procedure is provided to determine the optimal delivery and order policy. We conduct a numerical experiment and give sensitive analysis by varying some parameters to illustrate the problem and its solution procedure.

Coordinating lot sizing and integrated production and distribution scheduling with batch delivery and holding cost

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maedeh Bank ◽  
Mohammad Mahdavi Mazdeh ◽  
Mahdi Heydari ◽  
Ebrahim Teimoury
Keyword(s):  
Supply Chain ◽  
Lot Sizing ◽  
Mixed Integer ◽  
Time Interval ◽  
Content Type ◽  
Integrated Production ◽  
Holding Costs ◽  
Integrated Production And Distribution ◽  
Distribution Scheduling ◽  
Production And Distribution

PurposeThe aim of this paper is to present a method for finding the optimum balance between sequence-dependent setup costs, holding costs, delivery costs and delay penalties in an integrated production–distribution system with lot sizing decisions.Design/methodology/approachTwo mixed integer linear programming models and an optimality property are proposed for the problem. Since the problem is NP-hard, a genetic algorithm reinforced with a heuristic is developed for solving the model in large-scale settings. The algorithm parameters are tuned using the Taguchi method.FindingsThe results obtained on randomly generated instances reveal a performance advantage for the proposed algorithm; it is shown that lot sizing can reduce the average cost of the supply chain up to 11.8%. Furthermore, the effects of different parameters and factors of the proposed model on supply chain costs are examined through a sensitivity analysis.Originality/valueAlthough integrated production and distribution scheduling in make-to-order industries has received a great deal of attention from researchers, most researchers in this area have treated each order as a job processed in an uninterrupted time interval, and no temporary holding costs are assumed. Even among the few studies where temporary holding costs are taken into consideration, none has examined the effect of splitting an order at the production stage (lot sizing) and the possibility of reducing costs through splitting. The present study is the first to take holding costs into consideration while incorporating lot sizing decisions in the operational production and distribution problem.

scholarly journals The Single-Vendor Multibuyer Integrated Production-Delivery Model with Production Capacity under Stochastic Lead Time Demand

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Xuefang Sun
Keyword(s):  
Genetic Algorithm ◽  
Lead Time ◽  
Production Capacity ◽  
Solution Procedure ◽  
Managerial Implication ◽  
Optimal Production ◽  
Integrated Production ◽  
Delivery Model ◽  
Multiple Buyers ◽  
Exhaustive Method

In this paper, we consider an integrated production-delivery model in which a vendor supplies the same product to multiple buyers. Unlike existing study, in this proposed model, we assume that the sum of all buyers’ demand rates is larger than the vendor’s production rate under normal work, but less than that under overtime. All buyers are independent of each other. For each buyer, the lead time demand is stochastic and the shortage during lead time is permitted. The main objective of this model is to determine the optimal production and delivery policies and the optimal overtime strategy, which minimize the joint expected annual cost of the system. Based on the genetic algorithm, we develop a solution procedure to find the optimal production, delivery, and overtime decision of this model. Computational experiments show the error rate between the objective values obtained by the proposed solution procedure and the solutions solved by the exhaustive method. The results indicate that the proposed mixed genetic algorithm is more effective and adoptable in comparison with the exhaustive method as it can be able to calculate the optimal solutions for at least 96% for the instances. Ultimately, an adequate numerical example is given to show the detailed process of the solution procedure, and sensitivity analysis of main parameters with managerial implication is discussed.

scholarly journals Strategic planning of biodiesel supply chain

2017 ◽  
Vol 22 (1) ◽  
pp. 77-95 ◽  
Author(s):  
Rafael Guillermo García Cáceres
Keyword(s):  
Supply Chain ◽  
Economies Of Scale ◽  
Benders Decomposition ◽  
Production Capacity ◽  
Solution Procedure ◽  
Current Approach ◽  
Branch And Cut ◽  
Raw Material ◽  
Chance Constraint ◽  
Mip Model

Introduction:A stochastic biobjective MIP model for designing the network of biodiesel supply chains is presented. Ultimately intending to support the strategic decisions of stakeholders. The constraints included are: economies of scale, location of facilities, production capacity, raw material supply, product demand, bill of materials and mass balance.Objectives:The model aims to minimize, both, the total cost and environmental impact of five chain echelonsMetodology:The solution procedure resorts to chance constraint and the ε-constraint method to solve the biobjective model.Results:Computational experiments allowed assessing the performance of the solution procedure. The CPU times for the solution of the instances of the problem show very good values.Conclutions:By approaching the modeling of the biodiesel supply chain the current contribution can serve as the basis of future similar works and associated solution procedures, thus facilitating decision-making at different supply chain stages. The current approach can be improved through its modeling and/or through the development of solution procedures that allow its practical use in larger instances of the model. This can be overcome through permanent research lines that include the development of adequate acceleration methods, valid constraints, Benders decomposition, branch and cut, Lagrangian decomposition, Danzing-Wolf decomposition, or heuristics and meta-heuristics.

scholarly journals Effect of Carbon Emission and Human Errors on a Two-Echelon Supply Chain under Permissible Delay in Payments

2020 ◽  
Vol 5 (2) ◽  
pp. 225-236
Author(s):  
Manavi Gilotra ◽  
Sarla Pareek ◽  
Mandeep Mittal ◽  
Vinti Dhaka
Keyword(s):  
Supply Chain ◽  
Inventory Management ◽  
Trade Credit ◽  
Transportation Cost ◽  
Solution Procedure ◽  
Production Model ◽  
Type I ◽  
Human Errors ◽  
Economic Production ◽  
Delay In Payments

Environmental worries in production and inventory models have received large attention in inventory management literature. In this paper, an economic production model is proposed with two-echelon supply chain when trade credit is offered by the supplier. This paper proposes human errors of Type I and Type II due to fatigue and inexperience of the inspector during screening. It considers the use of energy for production along with greenhouse gases (GHG) emission from production and transportation operations. The developed model optimizes the environmental and economic performances of the supply chain. Our aim is to explore the effects of human errors during inspection on the emission cost, transportation cost and delay in payment on the replenishment of order sizes and the expected total profit of the retailer. A mathematical model is developed and numerical examples are provided to illustrate the solution procedure.

scholarly journals An Integrated Production-Distribution Planning Problem under Demand and Production Capacity Uncertainties: New Formulation and Case Study

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Taycir Ben Abid ◽  
Omar Ayadi ◽  
Faouzi Masmoudi
Keyword(s):  
Supply Chain ◽  
Real Life ◽  
Production Capacity ◽  
Planning Horizon ◽  
Planning Problem ◽  
Supply Chain Network ◽  
Distribution Planning ◽  
Integrated Production ◽  
Production Distribution

In this study, we propose to solve a biobjective tactical integrated production-distribution planning problem for a multisite, multiperiod, multiproduct, sea-air intermodal supply chain network under uncertainties. Two random parameters are considered simultaneously: product replenishment orders and production capacity, which are modelled via a finite set of scenarios, using a two-stage stochastic approach. A corresponding mathematical model is developed, coded, and solved using the LINGO 18.0 software optimisation tool. This model aims to simultaneously minimise the total costs of production in both regular and overtime, inventory, distribution, and backordering activities and maximise the customer satisfaction level over the tactical planning horizon. The AUGMECON technique is applied to handle with the multiobjective optimisation. The applicability and the performance of the proposed model are tested through a real-life case study inspired from a medium-sized Tunisian textile and apparel company. Sensitivity analysis on stochastic parameters and managerial insights for the studied supply chain network are argued based on the empirical findings.

Designing a sustainable supply chain network for producing high-value products from waste glass

2021 ◽  
pp. 0734242X2199466
Author(s):  
Naeme Zarrinpoor
Keyword(s):  
Supply Chain ◽  
Greenhouse Gas Emission ◽  
Fuzzy Programming ◽  
Solution Procedure ◽  
Waste Glass ◽  
Worker Safety ◽  
Programming Approach ◽  
Supply Chain Network ◽  
Sustainable Supply Chain ◽  
Proposed Model

This paper aims to design a supply chain network for producing double glazed glass from the recycling of waste glass. All three pillars of sustainability are taken into consideration. The economic objective tries to maximize total profits. The environmental objective considers the energy consumption, the generated waste, the greenhouse gas emission, the water consumption, and the fuel consumption of vehicles. The social objective addresses created job opportunities, the worker safety, the regional development, the worker benefit, and training hours. To solve the model, a two-stage framework based on the group best-worst method and an interactive fuzzy programming approach is developed. The proposed model is validated through a real case study based on waste glass management in the city of Shiraz. It is revealed that when sustainable development goals are approached, a great degree of improvement will be attained in environmental and social aspects without a significant decrease in the economic sustainability. The results also demonstrate that the locations of glass recycling centres are different under economic, environmental, and social pillars, and the proposed model yields an optimal system configuration with a proper satisfaction degree of all objectives. Moreover, applying the proposed solution procedure enables system designers to obtain the most desirable trade-off between different aspects of sustainability.

System dynamics model of production-inventory-routing system in the green supply chain

2021 ◽  
pp. 1-14
Author(s):  
Katayoun Naderi ◽  
Roya M. Ahari ◽  
Javid Jouzdani ◽  
Atefeh Amindoust
Keyword(s):  
Supply Chain ◽  
System Dynamics ◽  
Supply Chains ◽  
Transportation Cost ◽  
Green Supply Chain ◽  
Ideal Condition ◽  
Inventory Routing ◽  
Production Inventory ◽  
Fierce Competition ◽  
Maximum Production Rate

Fierce competition in the global markets forced companies to improve the design and management of supply chains, because companies are always looking for more profit and higher customer satisfaction. The emergence of the green supply chain is one of the most important developments of the last decade. It provides an opportunity for companies to adjust their supply chains according to environmental goals and sustainability. The integrated production-inventory-routing is a new field that aims to optimize these three decision-making levels. It can be described as follow: a factory produces one or more products, and sells them to several customers (by direct delivery or a specific customer chain). The current study aims to model a production-inventory-routing system using a system dynamics approach to design a green supply chain under uncertain conditions. For this purpose, first, the association between selected variables was determined. Then, the proposed model was validated. Finally, to identify variables with the highest influence, four scenarios were developed. The results indicated that minimum total transportation cost, the total warehouse capacity of the supply chain, and the maximum production rate are the most influential strategies to achieve ideal condition.

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