Integrated single vendor single buyer model with stochastic demand and variable lead time

Ben‐Daya, Mohamed; Hariga, Moncer

doi:10.1016/j.ijpe.2003.09.012

Cited by 219 publications

(94 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moon and Choi (1998) and Hariga and Ben-Daya (1999) further improved and revised Ouyang et al's model (1996) by optimizing the reorder point. The integrated inventory models under stochastic environment were developed by Ben-Daya and Hariga (2004), Ouyang et al (2004) and Jauhari et al (2011).…”

Section: Direct Emissionmentioning

confidence: 99%

Greenhouse gas penalty and incentive policies for a joint economic lot size model with industrial and transport emissions

Wangsa¹

2017

10.5267/j.ijiec

View full text Add to dashboard Cite

This paper presents a joint economic lot size model for a single manufacturer-a single buyer. The purposed model involves the greenhouse gas emission from industrial and transport sectors. We divide the emission into two types, namely the direct and indirect emissions. In this paper, we consider the Government's penalty and incentive policies to reduce the emission. We assume that the demand of the buyer is normally distributed and partially backordered. The objective is to minimize joint total cost incurred by a single manufacturer-a single buyer and involves the transportation costs of the freight forwarder. Transportation costs are the function of shipping weight, distance, fuel price and consumption with two transportation modes: truckload and lessthan-truckload shipments. Finally, an algorithm procedure is proposed to determine the optimal order quantity, safety factor, actual shipping weight, total emission and frequency of deliveries. Numerical examples and analyses are given to illustrate the results.

show abstract

Section: Direct Emissionmentioning

confidence: 99%

Greenhouse gas penalty and incentive policies for a joint economic lot size model with industrial and transport emissions

Wangsa¹

2017

10.5267/j.ijiec

View full text Add to dashboard Cite

show abstract

“…Ben-Daya and Hariga [2] extended this by taking the annual customer demand to be stochastic with variable lead time and thereby allowing shortages. Vandana, B.K.Sharma [13] allowing shortages and considered an economic ordered quantity model for retailers partial permissible delay in payment linked to order quantity.…”

Section: Literature Reviewmentioning

confidence: 99%

Single vendor-buyer integrated inventory system for imperfect production with variable lead time

Uthayakumar¹,

Kumar²

2016

ORAJ

View full text Add to dashboard Cite

In this paper, the authors considered the single vendor single buyer integrated production inventory problem with stochastic demand for an imperfect production process. They relax the assumption that, the lead time is varying linearly with the lot size. That is, the lead time is composed of a lot size dependent run time and constant delay times such as moving, waiting and setup times. A solution procedure is mentioned for solving the proposed model and numerical examples are used to illustrate the benefit of integration. A sensitivity analysis is also performed to explore the effect of key parameter D (demand). A simple procedure is suggested to obtain an approximate solution of the proposed model. Examples are used toillustrate the model and explore the effect of important parameters on the production schedule and total expected cost.

show abstract

“…Srinivas & Rao (2007) developed a controllable-lead-time inventory model where the lead time is assumed to be dependent because at the time of contract with a vendor (manufacturer), the buyer (retailer) may intend to reduce the lead time, for which he will pay an additional cost to accomplish an increased production rate. Ben-Daya & Hariga (2004) considered the single vendor single buyer integrated production inventory problem where demand is stochastic and the lead time is varying linearly with the lot size; i.e.,…”

Section: Stochastic Modelsmentioning

confidence: 99%

Quantitative Models for Centralised Supply Chain Coordination

Jaber¹,

Zolfaghari²

2008

Supply Chain

View full text Add to dashboard Cite

IntroductionA supply chain is defined as a network of facilities and distribution options that perform the functions of procurement of materials, transformation of these materials into intermediate and finished products, and the distribution of these finished products to customers. Managing such functions along the whole chain; that is, from the supplier's supplier to the customer's customer; requires a great deal of coordination among the players in the chain. The effectiveness of coordination in supply chains could be measured in two ways: reduction in total supply chain costs and enhanced coordination services provided to the end customer ⎯ and to all players in the supply chain. Inventory is the highest cost in a supply chain accounting for almost 50% of the total logistics costs. Integrating order quantities models among players in a supply chain is a method of achieving coordination. For coordination to be successful, incentive schemes must be adopted. The literature on supply chain coordination have proposed several incentive schemes for coordination; such as quantity discounts, permissible delay in payments, price discounts, volume discount, common replenishment periods. The available quantitative models in supply chain coordination consider up to four levels (i.e., tier-1 supplier, tier-2 supplier, manufacturer, and buyer), with the majority of studies investigating a two-level supply chain with varying assumptions (e.g., multiple buyers, stochastic demand, imperfect quality, etc). Coordination decisions in supply chains are either centralized or decentralized decision-making processes. A centralized decision making process assumes a unique decision-maker (a team) managing the whole supply chain with an objective to minimize (maximize) the total supply chain cost (profit), whereas a decentralized decision-making process involves multiple decision-makers who have conflicting objectives. This chapter will review the literature for quantitative models for centralised supply chain coordination that emphasize inventory management for the period from 1990 to end of 2007. In this chapter, we will classify the models on the basis of incentive schemes, supply chain levels, and assumptions. This chapter will also provide a map indicative of the limitations of the available studies and steer readers to future directions along this line of research. Centralised supply chain coordinationA typical supply chain consists of multistage business entities where raw materials and components are pushed forward from the supplier's supplier to the customer's customer. During this forward push, value is gradually added at each entity in the supply chain transforming raw materials and components to take their final form as finished products at the customer's end, the buyer. These business entities may be owned by the same organization or by several organizations. Goyal & Gupta (1989) suggested that coordination could be achieved by integrating lotsizing models. However, coordinating orders among players in a supply chain might...

show abstract

Integrated single vendor single buyer model with stochastic demand and variable lead time

Cited by 219 publications

References 12 publications

Greenhouse gas penalty and incentive policies for a joint economic lot size model with industrial and transport emissions

Greenhouse gas penalty and incentive policies for a joint economic lot size model with industrial and transport emissions

Single vendor-buyer integrated inventory system for imperfect production with variable lead time

Quantitative Models for Centralised Supply Chain Coordination

Contact Info

Product

Resources

About