The joint replenishment problem involving multiple suppliers offering quantity discounts

Moon, Ilkyeong; Goyal, S. K.; C., B.

doi:10.1080/00207720701832614

Cited by 33 publications

(10 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To manage collaboration in the supply chain for automotive industry efficiently, many strategic collaborative practices have been proposed, such as just-in-time (JIT) (Aigbedo 2007;Sandanayake et al 2008), original equipment manufacturing (OEM) (Schilli and Dai 2006), and outsourcing (Reeves Jr et al 2010;Moon et al 2008). Trust of participants is one of the most important factors for implementing these strategies and managing collaborative supply chains in the automotive industry.…”

Section: Assemblermentioning

confidence: 99%

Collaborative fractal-based supply chain management based on a trust model for the automotive industry

Ryu

Moon

et al. 2010

Flex Serv Manuf J

View full text Add to dashboard Cite

In the supply chain of the automotive industry, where the procurement ratio of parts from partners is very high, the trustworthiness of partners should be considered during supply chain optimization. In this paper, to deal with the trust issue related to collaboration and reduce the computational load in production planning, we develop a collaborative fractal-based supply chain management framework for the automotive industry. In our framework, the relationships between the participants of a supply chain are modeled as a fractal. Each fractal has a goal model and generates a production plan of its participants based on the goal model. The goal model of each fractal is developed from an operational perspective to consider the trust value of participants during production planning. A fuzzy trust evaluation model is used to evaluate the trust value in terms of numerical value. To validate the developed framework in the automotive industry, simulations are conducted. The results of the simulations indicate that our framework can be useful in generating precise production plans.

show abstract

Section: Assemblermentioning

confidence: 99%

Collaborative fractal-based supply chain management based on a trust model for the automotive industry

Ryu

Moon

et al. 2010

Flex Serv Manuf J

View full text Add to dashboard Cite

show abstract

“…At present, the research on joint ordering problem and algorithms has made great achievement [21][22][23][24][25][26]; most of them adopt heuristic algorithms to solve it, such as genetic algorithm (GA), particle swarm optimization (PSO), differential evolution algorithm (DE), and improved or hybrid algorithms. Furthermore, heuristic algorithms are combined with simulation methods.…”

Section: Jointmentioning

confidence: 99%

An Improved Swarm Intelligence Algorithm for Multi-Item Joint Ordering Strategy of Cruise Ship Supply

Huang

Yang

2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

From the perspective of the global value chain of the cruise industry, the output value of cruise operation accounts for 50%, with the highest added value, and cruise ship supply is the crucial link in cruise operation management, with substantial economic benefits. erefore, optimizing the purchasing process can not only save costs for cruise companies but also improve cruise level service. Aiming at the purchasing characteristics and modes of cruise ship supply, an optimization model of multi-item joint ordering is constructed under global cruise ship supply chain, considering different order cycles, integrated operation of purchase, delivery, and inventory based on a cruise distribution center. And an improved swarm intelligence algorithm, called fireworks algorithm with inertia weight (WFWA), is proposed for global optimization of the objective function. By comparing the optimization results with fireworks algorithm (FWA), genetic algorithm (GA), and particle swarm optimization (PSO) through experimental tests, it demonstrates that WFWA has higher optimization accuracy and better global convergence.

show abstract

“…By introducing the all-unit quantity discount to JRP , Cha and Moon [ 19 ] constructed a JRP model with quantity discounts and an efficient heuristic algorithm was developed to solve the proposed model. Moon et al [ 38 ] transformed the single supplier JRP with all-unit quantity discount to a multi-supplier and each item is assumed to be purchased from one supplier. Paul et al [ 2 ] formulated a JRP model considering the imperfect items and all-unit quantity discount.…”

Section: Literature Reviewmentioning

confidence: 99%

A novel multi-item joint replenishment problem considering multiple type discounts

et al. 2018

View full text Add to dashboard Cite

In business replenishment, discount offers of multi-item may either provide different discount schedules with a single discount type, or provide schedules with multiple discount types. The paper investigates the joint effects of multiple discount schemes on the decisions of multi-item joint replenishment. In this paper, a joint replenishment problem (JRP) model, considering three discount (all-unit discount, incremental discount, total volume discount) offers simultaneously, is constructed to determine the basic cycle time and joint replenishment frequencies of multi-item. To solve the proposed problem, a heuristic algorithm is proposed to find the optimal solutions and the corresponding total cost of the JRP model. Numerical experiment is performed to test the algorithm and the computational results of JRPs under different discount combinations show different significance in the replenishment cost reduction.

show abstract

The joint replenishment problem involving multiple suppliers offering quantity discounts

Cited by 33 publications

References 20 publications

Collaborative fractal-based supply chain management based on a trust model for the automotive industry

Collaborative fractal-based supply chain management based on a trust model for the automotive industry

An Improved Swarm Intelligence Algorithm for Multi-Item Joint Ordering Strategy of Cruise Ship Supply

A novel multi-item joint replenishment problem considering multiple type discounts

Contact Info

Product

Resources

About