A Conic Integer Programming Approach to Stochastic Joint Location-Inventory Problems

Atamtürk, Alper; Berenguer, Gemma; Shen, Zuo‐Jun Max

doi:10.1287/opre.1110.1037

Cited by 124 publications

(95 citation statements)

References 32 publications

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“…Fuzzy approaches are also applied by several LIP papers for the same purpose [50,89,99]. Some other articles [23,29,65,91,93,94,100,101] used the advantage of the probability distributions to address stochasticity, and the remaining models are deterministic.…”

Section: Location Inventory Problemsmentioning

confidence: 99%

The New Generation of Operations Research Methods in Supply Chain Optimization: A Review

Pourhejazy

Kwon

2016

Sustainability

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Abstract:The possibilities of applying Operations Research (O.R.) techniques in the design of real-world systems are vast. The optimization and design of the supply chain network (SCN) is one of the relevant topics that has directed the attention of many scholars. Sound decisions in this regard, including the proper selection of the facility's location, transportation modes and routes and inventory management policies, can noticeably improve the systems performance. Over 380 articles published between 2005 and 2016 in the ISI/Web of Science database have applied advanced O.R. techniques in SCN optimization studies. This paper offers a systematic review of these published contributions by focusing on two categories of O.R. approaches most recently applied for the design of SC systems: integrated mathematical modeling and simulation-optimization (S-O) frameworks. A taxonomy analysis of the mentioned approaches is presented based on the supply chain elements. A bibliometric analysis is also conducted to provide technical insights into the possible gaps in the field. Moreover, the relevant studies on SC sustainability are highlighted. The research results are supportive of the S-O frameworks as either an alternative approach or an effective solution method for the integrated problems. The research outcomes can provide researchers in the field with useful details of the integrated problems and S-O frameworks as the most recent O.R. methodologies in the field of SC optimization.

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Section: Location Inventory Problemsmentioning

confidence: 99%

The New Generation of Operations Research Methods in Supply Chain Optimization: A Review

Pourhejazy

Kwon

2016

Sustainability

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“…• In [3], Atamturk et al explore a joint facility location and inventory management model under stochastic retailer demand. The binary variables arise in the choice of candidate locations at which to open distribution centers and the assignment of retailers to the distribution centers.…”

Section: Misocps Arising In Applicationsmentioning

confidence: 99%

Smoothing and Regularization for Mixed-Integer Second-Order Cone Programming with Applications in Portfolio Optimization

Benson

Sağlam

2013

Springer Proceedings in Mathematics &Amp; Statistics

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Second-order cone programming problems (SOCPs) have been well studied in literature, and computationally efficient implementations of solution algorithms exist. In this paper, we study an extension: mixed-integer second-order cone programming problems (MISOCPs). Our focus is on designing an algorithm for solving the underlying SOCPs as nonlinear programming problems (NLPs) within two existing frameworks, branch-and-bound and outer approximation, for mixed-integer nonlinear programming (MINLP). We pay particular attention to resolving the nondifferentiability of the underlying SOCPs via a smoothing reformulation, as well as warmstarting and infeasibility detection using a regularization. We investigate the application of our proposed techniques to portfolio optimization problems that can be formulated as MISOCPs, and preliminary numerical results using the Matlab-based optimization package MILANO (Benson, MILANO-a Matlab-based code for mixed-integer linear and nonlinear optimization. http://www. pages.drexel.edu/~hvb22/milano) are provided.

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“…Daskin et al (2002), Miranda and Garrido (2004) and Shen et al (2003) were among the first to point out the interaction between the inventory and location models. A recent line of work, including the research by Teo and Shu (2004), Atamtürk et al (2012), Miranda and Garrido (2006), Ozsen et al (2008), Romeijn et al (2007), Shahabi et al (2014), Snyder et al (2007) and Tancrez et al (2012).…”

Section: Introductionmentioning

confidence: 99%

A bi-objective location inventory model for three-layer supply chain network design considering capacity planning

Iranmanesh

Kazemi

2017

IJLSM

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This paper aims at bi-objective optimisation of single product for three-layer supply chain network consisting of a factory, distribution centres (DCs) and customers including the impact of inventory management system. The key design decisions are: The location of DCs and their capacity, production capacity of the factory, product quantity to be transported from factory to each DC, product quantity to be transported from each DC to each customer, and order quantity at DCs, so as to minimise the sum of the production cost, location cost, transportation cost, ordering cost, inventory holding cost, and lost sales. The problem is formulated as a mixed-integer nonlinear programming (MINLP) model and solved using GAMS solver and proposed meta-heuristic algorithm. The ε-constraint method is used as solution approach to tackle the multi-objective problem when using GAMS. Because of NP-hardness of the problem, a hybrid meta-heuristic algorithm based on genetic algorithm is proposed to solve large scale problems. Computational experiments demonstrate the effectiveness of the proposed model and algorithm in designing large supply chain networks.Keywords: supply chain management; SCM; location inventory problem; capacity planning; meta-heuristic algorithm.Reference to this paper should be made as follows: Iranmanesh, H. and Kazemi, A. (2017) 'A bi-objective location inventory model for three-layer supply chain network design considering capacity planning', Int.

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A Conic Integer Programming Approach to Stochastic Joint Location-Inventory Problems

Cited by 124 publications

References 32 publications

The New Generation of Operations Research Methods in Supply Chain Optimization: A Review

The New Generation of Operations Research Methods in Supply Chain Optimization: A Review

Smoothing and Regularization for Mixed-Integer Second-Order Cone Programming with Applications in Portfolio Optimization

A bi-objective location inventory model for three-layer supply chain network design considering capacity planning

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