scholarly journals Designing a supply chain network under a dynamic discounting-based credit payment program

2021 ◽  
Author(s):  
Yu-Chung Tsao ◽  
Mutia Setiawati ◽  
Thuy Linh Vu ◽  
Andi Sudiarso
Keyword(s):  
Supply Chain ◽  
Linear Optimization ◽  
Cash Flows ◽  
Network Design Problem ◽  
Selling Price ◽  
Supply Chain Network ◽  
Credit Period ◽  
Solution Approach ◽  
Supply Chain Finance ◽  
Influence Area

This study examines the effects of dynamic discounting based credit payment on a supply chain network design problem. Dynamic discounting based credit payment is a supply chain finance policy wherein the supplier provides a credit period to a distribution center (DC) with a discount applied if the DC pays the supplier before the end of the credit period. This study also considers the time value of money and applies discounted cash flows to formulate a model that determines the DC’s optimal replenishment cycle, selling price, and influence area while maximizing the present value of the total profit. The continuous approximation approach is applied to formulate a mathematical model of the problems, and an algorithm based on non-linear optimization is established to solve the problem. A numerical example and a sensitivity analysis are provided to present the proposed model and solution approach and to illustrate the effect of each cost on the decisions and profit.

Solving a Two-stage Supply Chain Network Design Problem with Fixed Costs by a Hybrid Genetic Algorithm

2021 ◽  
Author(s):  
Ovidiu Cosma ◽  
Petrică C Pop ◽  
Cosmin Sabo
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Network Design ◽  
Design Problem ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Network Design Problem ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Fixed Costs

Abstract In this paper we investigate a particular two-stage supply chain network design problem with fixed costs. In order to solve this complex optimization problem, we propose an efficient hybrid algorithm, which was obtained by incorporating a linear programming optimization problem within the framework of a genetic algorithm. In addition, we integrated within our proposed algorithm a powerful local search procedure able to perform a fine tuning of the global search. We evaluate our proposed solution approach on a set of large size instances. The achieved computational results prove the efficiency of our hybrid genetic algorithm in providing high-quality solutions within reasonable running-times and its superiority against other existing methods from the literature.

Supply chain network design based on cost of quality and quality level analysis

2019 ◽  
Vol 31 (3) ◽  
pp. 467-490 ◽  
Author(s):  
Asama Alglawe ◽  
Andrea Schiffauerova ◽  
Onur Kuzgunkaya ◽  
Itad Shiboub
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Linear Optimization ◽  
Transportation Costs ◽  
Quality Level ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Content Type ◽  
Cost Of Quality ◽  
The Impact

Purpose The purpose of this paper is to explore the impact of the cost of quality (COQ) expenditure allocations on a capacitated supply chain (SC) network. Design/methodology/approach This paper proposes a non-linear optimization model which integrates the opportunity cost (OC) (i.e. customer satisfaction cost), into the COQ with consideration of the QL in the supply chain network design decisions. In addition, it examines the effect of considering an investment at each SC echelon to ensure the best overall QL. A numerical example is presented to illustrate the behavior of the model. Findings The results show how the QL, COQ and facility location decisions change when incorporating the OC, investments and transportation costs into the SC model. Originality/value The novelty of this paper is that it considers the effect of OC, investment at each echelon and transportation costs on SC design by minimizing the overall spending on the COQ. These issues have not been explored, and for that reason, this paper contributes to the understanding of the critical factors that optimizes the SC COQ.

scholarly journals Determining nodal capacities for military distribution problems

2019 ◽  
Vol 3 (2) ◽  
pp. 110-130 ◽  
Author(s):  
Dave C. Longhorn ◽  
Joshua R. Muckensturm
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
The United States ◽  
Network Design Problem ◽  
Mixed Integer ◽  
Multiple Time ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Content Type ◽  
Distribution Problems

Purpose This paper aims to introduce a new mixed integer programming formulation and associated heuristic algorithm to solve the Military Nodal Capacity Problem, which is a type of supply chain network design problem that involves determining the amount of capacity expansion required at theater nodes to ensure the on-time delivery of military cargo. Design/methodology/approach Supply chain network design, mixed integer programs, heuristics and regression are used in this paper. Findings This work helps analysts at the United States Transportation Command identify what levels of throughput capacities, such as daily processing rates of trucks and railcars, are needed at theater distribution nodes to meet warfighter cargo delivery requirements. Research limitations/implications This research assumes all problem data are deterministic, and so it does not capture the variations in cargo requirements, transit times or asset payloads. Practical implications This work gives military analysts and decision makers prescriptive details about nodal capacities needed to meet demands. Prior to this work, insights for this type of problem were generated using multiple time-consuming simulations often involving trial-and-error to explore the trade space. Originality/value This work merges research of supply chain network design with military theater distribution problems to prescribe the optimal, or near-optimal, throughput capacities at theater nodes. The capacity levels must meet delivery requirements while adhering to constraints on the proportion of cargo transported by mode and the expected payloads for assets.

scholarly journals A Robust Fuzzy Optimization Model for Closed-Loop Supply Chain Networks Considering Sustainability

2019 ◽  
Vol 11 (20) ◽  
pp. 5726 ◽  
Author(s):  
Xin Zhang ◽  
Gang Zhao ◽  
Yingxiu Qi ◽  
Botang Li
Keyword(s):  
Supply Chain ◽  
Social Impact ◽  
Closed Loop ◽  
Cost Minimization ◽  
Fuzzy Optimization ◽  
Three Dimensions ◽  
Strategic Decision ◽  
Supply Chain Network ◽  
Closed Loop Supply Chain ◽  
Solution Approach

Supply chain network design (SCND) is an important strategic decision determining the structure of each entity in the supply chain, which has an important impact on the long-term development of a company. An efficient and effective supply chain network is of vital importance for improving customer satisfaction, optimizing the allocation of resources, and increasing profitability. The environmental concerns and social responsibility awareness of the whole society have spurred researchers and managers to design sustainable supply chains (SSCs) integrating the economic, environmental, and social factors. In addition, the innate uncertainty of the SCND problem requires an integrated method to cope. In this regard, this study develops a multi-echelon multi-objective robust fuzzy closed-loop supply chain network (CLSCN) design model under uncertainty including all three dimensions of sustainability. This model considers the total cost minimization, carbon caps, and social impact maximization concurrently to realize supply chain sustainability, and is able to make a balance between the conflicting multiple objectives. Meanwhile, the uncertainty of the parameters is divided into two categories and addressed with two approaches: the first category is missed working days related to social impact, which is solved by the fuzzy membership theory; the second category is the demand and remanufacturing rate, which is settled by a robust optimization method. To validate the ability and applicability of the model and solution approach, a numerical example is conducted and solved using ILOG CPLEX. The result shows that the supply chain network structure and the value of the optimization objectives will change when considering sustainability and different degrees of uncertainty. This will enable supply chain managers to reduce the environmental impact and enhance the social benefits of their supply chain activities, and design a more stable supply chain to better cope with the influence of uncertainty.

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