scholarly journals Rolling Supply Chain Scheduling considering Suppliers, Production, and Delivery Lot-Size

2018 ◽  
Vol 2018 ◽  
pp. 1-14
Author(s):  
Rong-Hwa Huang ◽  
Tung-Han Yu ◽  
Chen-Yun Lee
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Simulated Data ◽  
Planning Horizon ◽  
Scheduling Problems ◽  
Supply Chain Scheduling ◽  
Lot Size ◽  
Delivery Cost ◽  
Chain Management ◽  
Rolling Planning

Supply chain management and integration play a key factor in contemporary manufacturing concept. Companies seek to integrate itself within a cooperative and mutual benefiting supply chain. Supply chain scheduling, as an important aspect of supply chain management, highly emphasizes on minimizing stock costs and delivery costs. Most previous researches on supply chain scheduling problems assume make-to-order production, which includes delivery cost in lot-size. This practice simplifies the complexity of the problem. Instead, this research discusses make-to-contract production, where the supply chain has a rolling planning horizon that changes according to contracts. Within a planning horizon, two types of interval are defined. The first is frozen interval, in which the manufacturing decision cannot be changed. The second is free interval, where schedules can be adjusted depending on new contracts. This research aims to build a robust rolling supply management schedule to satisfy customers’ needs, by considering supplier, production, and delivery lot-size simultaneously. The objective is to effectively decide a combination of supplier, production, and delivery lot-size that minimizes total cost consisting of supplier cost, finish good stock cost, and delivery cost. Based on the concept, this study designs a problem-solving process that combines the methods of rolling planning horizon and genetic algorithm. Delivery size (DS), finish good stock (FS), and early delivery cost (ED) are the three methods applied; each will provide a guideline to produce a feasible solution. By further considering the fluctuations in practical needs and performing an overall evaluation, a robust and optimal supply chain scheduling plan can be decided, including the optimal lot-sizes of supplier, production, and delivery. In the effectiveness test which considers 3 types of customer demands and 11 types of company cost structures, the simulated data test results suggest that the proposed methods in this study have excellent performance.

Metaheuristic Algorithms for Supply Chain Management Problems

2012 ◽  
pp. 1814-1837 ◽  
Author(s):  
Ata Allah Taleizadeh ◽  
Leopoldo Eduardo Cárdenas-Barrón
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Optimization Problems ◽  
Harmony Search ◽  
Metaheuristic Algorithms ◽  
Lot Size ◽  
Business Economics ◽  
Chain Management ◽  
Single Vendor ◽  
Partial Backordering

Recently, metaheuristic algorithms (MHAs) have gained noteworthy attention for their abilities to solve difficult optimization problems in engineering, business, economics, finance, and other fields. This chapter introduces some applications of MHAs in supply chain management (SCM) problems. For example, consider a multi-product multi-constraint SCM problem in which demands for each product are not deterministic, the lead-time varies linearly with regard to the lot-size and partial backordering of shortages are assumed. Thus, since the main goal is to determine the re-order point, the order quantity and number of shipments under the total cost of the whole chain is minimized. In this chapter, the authors concentrate on MHAs such as harmony search (HS), particle swarm optimization (PSO), genetic algorithm (GA), firefly algorithm (FA), and simulated annealing (SA) for solving the following four supply chain models: single-vendor single-buyer (SBSV), multi-buyers single-vendor (MBSV), multi-buyers multi-vendors (MBMV) and multi-objective multi-buyers multi-vendors (MOMBMV). These models typically are in any supply chain. For illustrative purposes, a numerical example is solved in each model.

The Bullwhip Effect

2014 ◽  
Vol 5 (1) ◽  
pp. 33-51 ◽  
Author(s):  
Yohannes Yebabe
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Inventory Management ◽  
Demand Management ◽  
Simulated Data ◽  
Bullwhip Effect ◽  
Customer Relationship ◽  
Causality Analysis ◽  
Chain Management ◽  
The Impact

Supply chain management is a fledgling science which concerned with synchronization of both material flow and information flow by integrating companies for a common objective to meet the requirements of the end customer. Bullwhip effect is an important research topic of the supply chain management. The Bullwhip effect is precarious to both short and long run competitive advantage, the dependability sustainability advantage of the chain. This paper proposes to show the impact of the Bullwhip effect on the supply chain using experimentally simulated data from Beer distribution game. The game represents a simple supply chain which consists of factory, distributor, wholesaler and retailer. The paper used empirical models of ANOVA, spectral density estimation, ARMAX and Cochrane- Orcutt autoregression. The result of the study prevails that when we quantify the impact of the Bullwhip effect to different actors of the supply chain with respect of inventory holding cost and stock-out case it is found that different cost implications. When quantifying the impact of the Bullwhip effect to the whole supply chain it is found that at least one of the competitive advantages of the chain is lost. When generalizing it the all the actors in the supply chain will suffer from the Bullwhip effect. The overall evidence from statistical causality analysis suggest that without proper both intra-organizational and inter-organizational coordination of the companies across the supply chain it is difficult to have effective and efficient customer relationship management, customer demand management and inventory management.

Metaheuristic Algorithms for Supply Chain Management Problems

2013 ◽  
pp. 110-135 ◽  
Author(s):  
Ata Allah Taleizadeh ◽  
Leopoldo Eduardo Cárdenas-Barrón
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Optimization Problems ◽  
Harmony Search ◽  
Metaheuristic Algorithms ◽  
Lot Size ◽  
Business Economics ◽  
Chain Management ◽  
Single Vendor ◽  
Partial Backordering

Recently, metaheuristic algorithms (MHAs) have gained noteworthy attention for their abilities to solve difficult optimization problems in engineering, business, economics, finance, and other fields. This chapter introduces some applications of MHAs in supply chain management (SCM) problems. For example, consider a multi-product multi-constraint SCM problem in which demands for each product are not deterministic, the lead-time varies linearly with regard to the lot-size and partial backordering of shortages are assumed. Thus, since the main goal is to determine the re-order point, the order quantity and number of shipments under the total cost of the whole chain is minimized. In this chapter, the authors concentrate on MHAs such as harmony search (HS), particle swarm optimization (PSO), genetic algorithm (GA), firefly algorithm (FA), and simulated annealing (SA) for solving the following four supply chain models: single-vendor single-buyer (SBSV), multi-buyers single-vendor (MBSV), multi-buyers multi-vendors (MBMV) and multi-objective multi-buyers multi-vendors (MOMBMV). These models typically are in any supply chain. For illustrative purposes, a numerical example is solved in each model.

scholarly journals Effects of Unequal Lot Size and Variable Transportation in Unreliable Supply Chain Management

Mathematics ◽  
2020 ◽  
Vol 8 (3) ◽  
pp. 357 ◽  
Author(s):  
Soumya Kanti Hota ◽  
Biswajit Sarkar ◽  
Santanu Kumar Ghosh
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Cost Reduction ◽  
Lead Time ◽  
Carbon Emission ◽  
Optimization Technique ◽  
Lot Size ◽  
Setup Cost ◽  
Chain Management ◽  
Special Cases

The effect of unreliable players on the supply chain management with a single-setup-multi-unequal-increasing-delivery-policy (SSMUID) along with a service-dependent demand and investment is discussed in this model. The manufacturer is unreliable which causes an increase of lead time and shortage. For solving the shortage problem and reducing lead time crashing cost (LTCC), an investment is utilized with the variable backorder price discounts. The number of transportation increases due to the new transportation policy and it causes pollution. Besides the fixed transportation and carbon emission cost (FTCEC), a container dependent carbon emission cost is applied. Some investments for setup cost reduction (SCR), ordering cost reduction (OCR), and quality improvement (QI) are considered. The lead time demand follows a normal distribution. The total cost of the supply chain is optimized and the model is tested numerically. The main intent of this study is to solve the shortage problem which occurs due to unreliability of the manufacturer. The study helps to reduce the unreliability issue of the manufacturer. The objective function is solved by using the classical optimization technique. Numerical results show that the discount for partial backorder enhances the profitability of the manufacturer. The sensitiveness of the parameters are discussed through the sensitivity of analysis and some special cases. Managerial insights provide the applicability of this study among different sectors.

Medikamentenlogistik: Kooperation: Swisslog Healthcare und SPZ

2017 ◽  
Vol 22 (04) ◽  
pp. 78-78
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Chain Management

Swisslog, ein führender Anbieter von Lösungen für Medikamenten- und Supply-Chain-Management im Gesundheitswesen, hat vom angesehenen Schweizer Paraplegiker-Zentrum in Nottwil (SPZ) den Großauftrag für die Lieferung und Installation seiner modernsten Technologie zur stationären und ambulanten Medikamentenversorgung erhalten.

Theory of the firm, Supply Chain management, and relationship marketing

2014 ◽  
pp. 40-60
Author(s):  
M. Storchevoy
Keyword(s):  
Economic Theory ◽  
Supply Chain ◽  
Supply Chain Management ◽  
Relationship Marketing ◽  
Theory Of The Firm ◽  
Chain Management

The paper studies through the lens of the economic theory of the firm the development of two managerial disciplines: supply chain management and relationship marketing. The author demonstrates which ideas have been borrowed by these disciplines from the economic theory of the firm, and in what extent their implications may be useful for the latter.

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