Integrated production/distribution planning in supply chains: An invited review

Erengüç, Ş. Selçuk; Simpson, Natalie; Vakharia, Asoo J.

doi:10.1016/s0377-2217(98)90299-5

Cited by 458 publications

(182 citation statements)

References 66 publications

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“…With several survey papers available, e.g., [5,8,13,26], we refer the reader to the most recent review by Chen [6]. The results related to our study fall in the category of "batch delivery by direct shipping" discussed in Section 5.1 of the review.…”

Section: Introductionmentioning

confidence: 88%

Tabu search and lower bounds for a combined production–transportation problem

Condotta

Knust

Meier

et al. 2013

Computers & Operations Research

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In this paper we consider a combined production-transportation problem, where n jobs have to be processed on a single machine at a production site before they are delivered to a customer. At the production stage, for each job a release date is given; at the transportation stage, job delivery should be completed not later than a given due date. The transportation is done by m identical vehicles with limited capacity. It takes a constant time to deliver a batch of jobs to the customer. The objective is to find a feasible schedule minimizing the maximum lateness.After formulating the considered problem as a mixed integer linear program, we propose different methods to calculate lower bounds. Then we describe a tabu search algorithm which enumerates promising partial solutions for the production stage. Each partial solution is complemented with an optimal transportation schedule (calculated in polynomial time) achieving a coordinated solution to the combined productiontransportation problem. Finally, we present results of computational experiments on randomly generated data.

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Section: Introductionmentioning

confidence: 88%

Tabu search and lower bounds for a combined production–transportation problem

Condotta

Knust

Meier

et al. 2013

Computers & Operations Research

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“…For example, a multi-objective programming model is proposed in [2], [11] to analyze solid waste management. The model for simultaneously optimizing the operations of both integrated logistics and its corresponding used-product reverse logistics in a close-looped supply chain has been presented in [12]. The common feature of these problems is the number of decision variables resulting from the allocation of resources, choice of location, route selection, choice of factory and distribution center, choise o mode of transport etc.…”

Section: Literature Review Of Supply Chains Models and Multi-objementioning

confidence: 99%

A Hybrid Multi-Objective Programming Framework for Modeling and Optimization of Supply Chain Problems

Sitek¹

2015

Annals of Computer Science and Information Systems

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Abstract-This paper presents a hybrid programming framework for solving multi-objective optimization problems in supply chain. The proposed approach consists of the integration and hybridization of two modeling and solving environments, i.e., constraint logic programming and mathematical programming, to obtain a programming framework that offers significant advantages over the classical approach derived from operational research. The strongest points of both components are combined in the hybrid framework, which by introducing transformation allows a significant reduction in size of a problem and the optimal solution is found a lot faster. This is particularly important in the multi-objective optimization where problems have to be solved over and over again to find a set of Pareto-optimal solutions. An over two thousand-fold reduction in size was obtained for the illustrative examples together with a few hundred-fold reduction in the speed of finding the solution in relation to the mathematical programming method. In addition, the proposed framework allows the introduction of logical constraints that are difficult or impossible to model in operational research environments.

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“…In each iteration of the relaxation algorithm, the transportation subproblem is used for coming up with a feasible solution. The goal is to find A t and B t that meet constraints (5) and (6). For each period, the items produced are allocated inside low cost containers whenever possible.…”

Section: Smoothing Procedure: Container Constraintsmentioning

confidence: 99%

“…Erenguç et al (1999) and Rizk & Martel (2001) present a general review of integrated production/distribution problems and Bertazzi & Speranza (1999) present a review considering extensions of the classical lot-sizing model for transportation cost models.…”

Section: Introductionmentioning

confidence: 99%

An approach using Lagrangian/surrogate relaxation for lot-sizing with transportation costs

et al. 2009

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The aim of this work was to study a distribution and lot-sizing problem that considers costs with transportation to a company warehouse as well as, inventory, production and setup costs. The logistic costs are associated with necessary containers to pack produced items. The company negotiates a long-term contract in which a fixed cost per period is associated with the transportation of the items. On the other hand, a limited number of containers are available with a lower cost than the average cost. If an occasional demand increase occurs, other containers can be utilized; however, their costs are higher. A mathematical model was proposed in the literature and solved using the Lagrangian heuristic. Here, the use of the Lagrangian/ surrogate heuristic to solve the problem is evaluated. Moreover, an extension of the literature model is considered adding capacity constraints and allowing backlogging. Computational tests show that Lagrangian/ surrogate heuristics are competitive, especially when the capacity constraints are tight.Keywords: lot-sizing; transportation costs; Lagrangian/surrogate relaxation. ResumoNeste trabalho estuda-se um problema de dimensionamento de lotes e distribuição que envolve além de custos de estoques, produção e preparação, custos de transportes para o armazém da empresa. Os custos logísticos estão associados aos contêineres necessários para empacotar os produtos produzidos. A empresa negocia um contrato de longo prazo onde um custo fixo por período é associado ao transporte dos itens, em contrapartida um limite de contêineres é disponibilizado com custo mais baixo que o custo padrão. Caso ocorra um aumento ocasional de demanda, novos contêineres podem ser utilizados, no entanto, seu custo é mais elevado. Um modelo matemático foi proposto na literatura e resolvido utilizando uma heurística Lagrangiana. No presente trabalho a resolução do problema por uma heurística Lagrangiana/surrogate é avaliada. Além disso, é considerada uma extensão do modelo da literatura adicionando restrições de capacidade e permitindo atraso no atendimento a demanda. Testes computacionais mostraram que a heurística Lagrangiana/surrogate é competitiva especialmente quando se têm restrições de capacidade apertada.Palavras-chave: dimensionamento de lotes; custos de transporte; relaxação Lagrangiana/surrogate.

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Integrated production/distribution planning in supply chains: An invited review

Cited by 458 publications

References 66 publications

Tabu search and lower bounds for a combined production–transportation problem

Tabu search and lower bounds for a combined production–transportation problem

A Hybrid Multi-Objective Programming Framework for Modeling and Optimization of Supply Chain Problems

An approach using Lagrangian/surrogate relaxation for lot-sizing with transportation costs

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