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

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.

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The impact of the cost of quality on serial supply‐chain network design

International Journal of Production Research ◽

10.1080/00207543.2011.649802 ◽

2012 ◽

Vol 50 (19) ◽

pp. 5544-5566 ◽

Cited By ~ 20

Author(s):

Krystel K. Castillo-Villar ◽

Neale R. Smith ◽

James L. Simonton

Keyword(s):

Supply Chain ◽

Network Design ◽

Supply Chain Network Design ◽

Supply Chain Network ◽

Cost Of Quality ◽

The Cost ◽

The Impact

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Determining nodal capacities for military distribution problems

Journal of Defense Analytics and Logistics ◽

10.1108/jdal-03-2019-0006 ◽

2019 ◽

Vol 3 (2) ◽

pp. 110-130 ◽

Cited By ~ 1

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.

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Design and Optimization of Capacitated Supply Chain Networks Including Quality Measures

Mathematical Problems in Engineering ◽

10.1155/2014/218913 ◽

2014 ◽

Vol 2014 ◽

pp. 1-17 ◽

Cited By ~ 8

Author(s):

Krystel K. Castillo-Villar ◽

Neale R. Smith ◽

José F. Herbert-Acero

Keyword(s):

Supply Chain ◽

Network Design ◽

Optimization Methods ◽

Mixed Integer ◽

Computational Time ◽

Quality Level ◽

Supply Chain Network Design ◽

Supply Chain Network ◽

Quality Costs ◽

Business Entities

This paper presents (1) a novel capacitated model for supply chain network design which considers manufacturing, distribution, and quality costs (named SCND-COQ model) and (2) five combinatorial optimization methods, based on nonlinear optimization, heuristic, and metaheuristic approaches, which are used to solve realistic instances of practical size. The SCND-COQ model is a mixed-integer nonlinear problem which can be used at a strategic planning level to design a supply chain network that maximizes the total profit subject to meeting an overall quality level of the final product at minimum costs. The SCND-COQ model computes the quality-related costs for the whole supply chain network considering the interdependencies among business entities. The effectiveness of the proposed solution approaches is shown using numerical experiments. These methods allow solving more realistic (capacitated) supply chain network design problems including quality-related costs (inspections, rework, opportunity costs, and others) within a reasonable computational time.

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Developing a meat supply chain network design using a multi-objective possibilistic programming approach

British Food Journal ◽

10.1108/bfj-10-2016-0475 ◽

2017 ◽

Vol 119 (3) ◽

pp. 690-706 ◽

Cited By ~ 17

Author(s):

Ahmed Mohammed ◽

Qian Wang

Keyword(s):

Supply Chain ◽

Network Design ◽

Meat Products ◽

Supply Chain Network Design ◽

Supply Chain Network ◽

Content Type ◽

Multi Objective ◽

Possibilistic Programming ◽

Conflicting Objectives ◽

Solution Methods

Purpose The purpose of this paper is to present a study in developing a cost-effective meat supply chain network design aiming to minimizing the total cost of transportation, the number of transportation vehicles and the delivery time of meat products. The developed model was also used for determining the optimum numbers and allocations of farms and abattoirs that need to be established and the optimal quantity flow of livestock from farms to abattoirs and meat products from abattoirs to retailers. Design/methodology/approach A multi-objective possibilistic programming model was formulated with a focus on minimizing the total cost of transportation, the number of transportation vehicles and the delivery time of meat products. Three sets of Pareto solutions were obtained using the three different solution methods. These methods are the LP-metrics method, the ɛ-constraint method and the weighted Tchebycheff method, respectively. The TOPSIS method was used for seeking a best Pareto solution as a trade-off decision when optimizing the three conflicting objectives. Findings A case study was also applied for examining the effectiveness and applicability of the developed multi-objective model and the proposed solution methods. The research concludes that the ɛ-constraint method has the superiority over the other two proposed methods as it offers a better solution outcome. Research limitations/implications This work addresses as interesting avenues for further research on exploring the delivery planner under different types of uncertainties and transportation means. Also, environmentalism has been increasingly becoming a significant global problem in the present century. Thus, the presented model could be extended to include the environmental aspects as an objective function. Practical implications The developed design methodology can be utilized for food supply chain designers. Also, it could be applied to realistic problems in the field of supply chain management. Originality/value The paper presents a methodology that can be used for tackling a multi-objective optimization problem of a meat supply chain network design. The proposed optimization method has the potential in solving the similar issue providing a compromising solution due to conflicting objectives in which each needs to be achieved toward an optimum outcome to survive in the competitive sector of food supply chains network.

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The Impact of Carbon Policies on Closed-loop Supply Chain Network Design

Procedia CIRP ◽

10.1016/j.procir.2014.07.042 ◽

2015 ◽

Vol 26 ◽

pp. 335-340 ◽

Cited By ~ 28

Author(s):

M. Fareeduddin ◽

Adnan Hassan ◽

M.N. Syed ◽

S.Z. Selim

Keyword(s):

Supply Chain ◽

Network Design ◽

Closed Loop ◽

Supply Chain Network Design ◽

Supply Chain Network ◽

Closed Loop Supply Chain ◽

The Impact

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The Impact of Carbon Emissions Policies on Reverse Supply Chain Network Design

Doğuş Üniversitesi Dergisi ◽

10.31671/dogus.2018.17 ◽

2018 ◽

Vol 1 (19) ◽

pp. 99-111 ◽

Cited By ~ 2

Author(s):

Bandar A. ALKHAYYAL ◽

Surendra M. GUPTA

Keyword(s):

Supply Chain ◽

Network Design ◽

Carbon Emissions ◽

Supply Chain Network Design ◽

Supply Chain Network ◽

Reverse Supply Chain ◽

The Impact

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Swarm intelligence approaches in supply chain management: potentials, challenges and future research directions

Supply Chain Management An International Journal ◽

10.1108/scm-02-2018-0070 ◽

2019 ◽

Vol 24 (1) ◽

pp. 107-123 ◽

Cited By ~ 5

Author(s):

Gunjan Soni ◽

Vipul Jain ◽

Felix T.S. Chan ◽

Ben Niu ◽

Surya Prakash

Keyword(s):

Linear Programming ◽

Supply Chain ◽

Supply Chain Management ◽

Network Design ◽

Optimization Problems ◽

Supply Chain Network Design ◽

Supply Chain Network ◽

Supply Chain Optimization ◽

Chain Management ◽

Content Type

Purpose It is worth mentioning that in supply chain management (SCM), managerial decisions are often based on optimization of resources. Till the early 2000s, supply chain optimization problems were being addressed by conventional programming approaches such as Linear Programming, Mixed-Integer Linear Programming and Branch-and-Bound methods. However, the solution convergence in such approaches was slow. But with the advent of Swarm Intelligence (SI)-based algorithms like particle swarm optimization and ant colony optimization, a significant improvement in solution of these problems has been observed. The purpose of this paper is to present and analyze the application of SI algorithms in SCM. The analysis will eventually lead to development of a generalized SI implementation framework for optimization problems in SCM. Design/methodology/approach A structured state-of-the-art literature review is presented, which explores the applications of SI algorithms in SCM. It reviews 56 articles published in peer-reviewed journals since 1999 and uses several classification schemes which are critical in designing and solving a supply chain optimization problem using SI algorithms. Findings The paper revels growth of swarm-based algorithms and seems to be dominant among all nature-inspired algorithms. The SI algorithms have been used extensively in most of the realms of supply chain network design because of the flexibility in their design and rapid convergence. Large size problems, difficult to manage using exact algorithms could be efficiently handled using SI algorithms. A generalized framework for SI implementation in SCM is proposed which is beneficial to industry practitioners and researchers. Originality/value The paper proposes a generic formulation of optimization problems in distribution network design, vehicle routing, resource allocation, inventory management and supplier management areas of SCM which could be solved using SI algorithms. This review also provides a generic framework for SI implementation in supply chain network design and identifies promising emerging issues for further study in this area.

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