Analysis of the maximum level policy in a production-distribution system

Archetti, Claudia; Bertazzi, Luca; Paletta, Giuseppe; Speranza, Maria

doi:10.1016/j.cor.2011.03.002

Cited by 126 publications

(128 citation statements)

References 17 publications

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“…Table 3 indicates that Tactical Planning is the most studied planning/decision level. (Chandra, 1993), (Martin et al,1993), (Fisher & Chandra, 1994), (Chen & Wang, 1997), (Mcdonald & Karimi, 1997), (Lucas et al, 2001), (Sakawa et al, 2001), (Gupta & Maranas, 2003), (Ryu et al,2004), (Bertazzi et al,2005), (Lei et al,2006), (Oh & Karimi, 2006), (Roghanian et al,2007), (Park(a), 2007), (Dhaenens-Flipo & Finke, 2001), (Liang, 2007), (Boudia(a) et al,2007), (Selim et al, 2008), (Jung et al,2008), (Torabi & Hassini, 2008), (Boudia (a) et al,2008) (Chen et al,2009), (Çetinkaya et al,2009), (Leung & Chan, 2009), (Safaei et al,2010) ,(Bard(c) & Nananukul(c), 2010) , (Shiguemoto & Armentano, 2010), (Ozdamar & Yazgac, 2010), (Lee(b) et al,2010), (Fahimnia et al,2015), (Archetti et al,2011), (Armentanoa et al,2011),(Mirzapour et al, 2011, (Jolaia et al,2011), (Amorim et al,2013), (Khakdaman et al,2014), (Khakdaman et al,2014), (Zhang et al,2014) , (Adulyasak et al,2014), ...…”

Section: Review Of the Work According To "Decisions Levels"mentioning

confidence: 99%

“…Table 4, classifies the works reviewed according to supply chain optimization topics. (Chandra, 1993), (Stacey et al,2007) x x (Martin et al,1993), (Fumero & Vercellis, 1999), (Timpe & x x x Kallrath, 2000), (Lei et al,2006), (Shiguemoto & Armentano, 2010), (Fahimnia et al,2015) (Fisher & Chandra, 1994), (Chen & Wang, 1997), (Sakawa et al,2001), (Ryu et al,2004), (Bertazzi et al,2005), (Oh & Karimi, 2006), (Roghanian et al,2007), (Park(a), 2007), (Dhaenens-Flipo & Finke, 2001), (Liang, 2007), (Boudia(a) et al, 2007), (Selim et al,2008), (Boudia (a) (Archetti et al, 2011), (Armentanoa et al,2011), (Chen et al,2009), (Amorim et al,2013), (Bilgen & Çelebi, 2013), (Nasiri et al,2014), (Adulyasak et al,2014) x x (Mcdonald & Karimi, 1997), (Gupta & Maranas, 2003), (Torabi & Hassini, 2008), (Khakdaman et al,2014), (Leung & Chan, 2009), (Mirzapour et al,2011, (Brahimia & Aouamb, 2015), (Shi et al,...…”

Section: Review Of the Work According To "Supply Chain Optimization mentioning

confidence: 99%

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Supply Chain Optimization Studies: A Literature Review and Classification

Kocaoğlu¹,

Gümüş²

2018

dogus

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Supply chain planning is an integrated process in which a group of several organizations, such as suppliers, producers, distributors and retailers, work together. It comprises procurement, production, distribution and demand planning topics. These topics require taking strategical, tactical and operational decisions. This research aims to reveal which supply chain topics, which decision levels, and which optimization methods are mostly studied in supply chain planning. This paper presents a total of 77 reviewed works published between 1993 and 2016 about supply chain planning. The reviewed works are categorized according to following elements: decision levels, supply chain optimization topics, objectives, optimization models.

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Section: Review Of the Work According To "Decisions Levels"mentioning

confidence: 99%

Section: Review Of the Work According To "Supply Chain Optimization mentioning

confidence: 99%

Supply Chain Optimization Studies: A Literature Review and Classification

Kocaoğlu¹,

Gümüş²

2018

dogus

View full text Add to dashboard Cite

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“…Production capacity and depot inventory capacity were set accordingly in [10] while uncapacitated production and unlimited depot inventory capacity were assumed in [9]. We keep the settings of initial inventory level, production capacity, and depot inventory capacity as those of [10], while taking the vehicle capacity as given in [9].…”

Section: Data and Experiments Settingsmentioning

confidence: 99%

“…The data set of [10] was created from a subset of the dataset of [9] for the PRP, which consists four classes of instances. Five instances with different node coordinates were generated for each instance type.…”

Section: Data and Experiments Settingsmentioning

confidence: 99%

“…After the importance of considering production, inventory, and routing decisions simultaneously was stressed in [7], the PRP was extended in various ways to consider, for example, multiple plants and heterogeneous fleets of vehicles [8], incapacitated production [9], multiple homogeneous capacitated vehicles [10], demand uncertainty [11], multi-item back-order [12], perishable products [13], and multiscale production [14] in the past decade. The environmental impact of the PRP has seldom…”

Section: Introductionmentioning

confidence: 99%

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Reducing Carbon Emissions in a Closed-Loop Production Routing Problem with Simultaneous Pickups and Deliveries under Carbon Cap-and-Trade

Fang

Qiu

2017

Sustainability

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Abstract:The incorporation of reverse logistics into production routing problems can promote and coordinate the implementation of sustainable development for supply chains. This study aims to incorporate reverse logistics into production routing problems and investigate the reduction of carbon emissions under carbon cap-and-trade. Mixed-integer programming models are proposed for the production routing problem with reverse logistics by considering simultaneous pickups and deliveries in vehicle routing subproblems. To solve this problem, we propose a solution method of a branch-and-cut guided search algorithm based on adaptation of known valid inequalities. Computational results highlight the trade-offs among various performance indicators, including emission levels and operational costs of production, inventory holding, fuel consumption, and drivers.

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The consistent production routing problem

2022

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This article introduces the consistent production routing problem in a setting with multiple plants and products. The problem consists in finding minimum‐cost production‐routing plans that also meet specific consistency requirements. In our context, consistency is defined as the degree to which some specified features of the solution remain invariant over time. We consider four forms of consistency, namely: driver, source, product, and plant consistency. For each of these consistency requirements, there is a target maximum value defining the decision‐maker's tolerance to deviations from a perfectly consistent solution. These targets are enforced as soft constraints whose violations need to be minimized when optimizing the integrated production and routing plan. We present a mathematical formulation for the problem and an exact branch‐and‐cut algorithm, enhanced with valid inequalities and specific branching priorities. We also propose a heuristic solution method based on iterated local search and several mathematical programming components. Experiments on a large benchmark set of newly introduced instances show that the enhancements substantially improve the performance of the exact algorithm and that the heuristic method performs robustly for production routing problems with different consistency requirements as well as for standard versions of the problem. We also analyze the cost‐consistency trade‐off of the solutions, confirming that it is possible to impose consistency without excessively increasing the cost. The results also reveal the impact of the first time period when optimizing and measuring the consistency features we study.

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Analysis of the maximum level policy in a production-distribution system

Cited by 126 publications

References 17 publications

Supply Chain Optimization Studies: A Literature Review and Classification

Supply Chain Optimization Studies: A Literature Review and Classification

Reducing Carbon Emissions in a Closed-Loop Production Routing Problem with Simultaneous Pickups and Deliveries under Carbon Cap-and-Trade

The consistent production routing problem

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