Modelling of transport costs and logistics for on-farm milk segregation in New Zealand dairying

Dooley, A.E.; Parker, W. J.; Blair, Hugh T.

doi:10.1016/j.compag.2004.12.007

Cited by 32 publications

(20 citation statements)

References 2 publications

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“…The multi-compartment VRP allows the transport of different types of goods in separate compartments in the same vehicle. Applications of VRPs with multiple compartments can be found in the distribution of petrol (different types of petrol transported in one vehicle) (e.g., Brown and Graves 1981;Cornillier et al 2008a) and food (e.g., a refrigerated compartment and a regular compartment in one vehicle) (Chajakis and Guignard 2003), waste collection (Muyldermans and Pang 2010), on-farm milk collection (Dooley et al 2005) and ship scheduling (Fagerholt and Christiansen 2000a).…”

Section: Allocation Constraintsmentioning

confidence: 99%

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Vehicle routing problems with loading constraints: state-of-the-art and future directions

et al. 2014

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Distributors are faced with loading constraints in their route planning, e.g.,multi-dimensional packing constraints, unloading sequence constraints, stability constraints and axle weight limits. Ignoring these constraints impairs planning and induces last-minute changes resulting in additional costs. Developing vehicle routing models incorporating loading constraints is critical to more efficient route planning. The last couple of years has seen a huge increase of contributions to this field of research with almost 60 % of these being published after 2009. Our contribution is twofold. First, we overview the recent developments in the literature on all vehicle types in which loading constraints play a key role (trucks, airplanes, ships, and automated guided vehicles), using a state-of-the-art classification scheme to identify the loading constraints considered in each article. Second, we identify research gaps and opportunities for future research.

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Section: Allocation Constraintsmentioning

confidence: 99%

“…Approximation schemes based on Langrangian relaxation are presented to solve these problems exactly for instances with up to 240 customers. Dooley et al (2005) use a GA for the on-farm collection problem of milk. The model may be used to evaluate alternative transport management strategies with regard to milk collection.…”

Section: Multi-compartments Vrpmentioning

confidence: 99%

Vehicle routing problems with loading constraints: state-of-the-art and future directions

et al. 2014

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“…Azaron et al (2005) study the problem of optimising PERT networks where the objective consists of competing terms that represent the completion time and direct cost. Dooley et al (2005) utilise GAs for optimising transportation of two types of milk from farms in New Zealand that included modelling the varying sizes of farms, the road networks and taking account of the collection costs as well as the revenues. Alba et al (2007) utilise GAs for planning software projects and consider the impact of various factors on the outcomes.…”

Section: Gas In Schedulingmentioning

confidence: 99%

A survey of AI in operations management from 2005 to 2009

Kobbacy

Vadera

2011

Journal of Manufacturing Technology Management

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Purpose: The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence this paper presents a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research.Design/methodology/approach: The paper builds upon our previous survey of this field which was carried out for the 10 year period 1995 to 2004(Kobbacy et al. 2007. Like the previous survey, it uses the Elsevier's ScienceDirect database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus the application categories adopted are: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Research on utilising neural networks, case based reasoning, fuzzy logic, knowledge based systems, data mining, and hybrid AI in the four application areas are identified. Findings:The survey categorises over 1400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: (a) The trends for Design and Scheduling show a dramatic increase in the use of GAs since 2003-04 that reflect recognition of their success in these areas, (b) A significant decline in research on use of KBS, reflecting their transition into practice, (c) an increasing trend in the use of fuzzy logic in Quality, Maintenance and Fault Diagnosis, (d) surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research.Originality/value: This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research.

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“…Dayarian (2014), T. Du (2007), A.E. Dooley (2005), A. Hoff (2007), Hui Juan Ma (2012), M. Jafari-Eskandari (2010), N. Lahrichi (2012), D.S.…”

Section: Literature Reviewmentioning

confidence: 99%

Integration of SCOR-Modeling and Logistical Concept of Management in the System of Internal Transportation of Milk Cooperative

Velychko¹

2015

MJSS

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Modelling of transport costs and logistics for on-farm milk segregation in New Zealand dairying

Cited by 32 publications

References 2 publications

Vehicle routing problems with loading constraints: state-of-the-art and future directions

Vehicle routing problems with loading constraints: state-of-the-art and future directions

A survey of AI in operations management from 2005 to 2009

Integration of SCOR-Modeling and Logistical Concept of Management in the System of Internal Transportation of Milk Cooperative

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