An evolutionary algorithm for optimizing material flow in supply chains

Vergara, Fernando; Khouja, Moutaz; Michalewicz, Zbigniew

doi:10.1016/s0360-8352(02)00055-4

Cited by 59 publications

(29 citation statements)

References 10 publications

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“…Vergara et al [57] developed a heuristic Evolutionary Algorithm (EA) for scheduling the part processes within the suppliers and setting the synchronized delivery cycle time for the supply chain. They compared the results with enumeration of all solutions and showed that the heuristic solution provides optimal or near-optimal solutions faster than enumeration methods as the problem size gets larger.…”

Section: Solution Methodologiesmentioning

confidence: 99%

Development of a Simultaneous Design for Supply Chain Process for the Optimization of the Product Design and Supply Chain Configuration Problem

Gokhan¹

2010

Engineering Management Journal

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iv This research investigates the development of a process for Design for Supply Chain (DFSC) -a process that aims to reduce the product life cycle costs, improve product quality, improve efficiency, and improve profitability for all partners in the supply chain (SC). It focuses on understanding the impacts and benefits of incorporating the SC configuration problem into the product design phase. As the product design establishes different requirements on the manufacturability, cost, and similar parameters, the SC is also closely linked to product design decisions and impacted by them. This research uniquely combines the impacts of the product design and price decisions on the product demand and the impacts of the SC decisions on cost, lead time, and demand satisfaction.The developed mathematical models are aimed at economically managing the SC for product design and support not only product design, but also redesign associated with process improvements and design changes in general. This research suggests development of a proactive approach to product design allowing impacts to the SC to be predicted in advance and resolved more quickly and economically. It presents two product and SC design approaches. The sequential approach examines the design of a product followed by the SC design where the simultaneous approach considers both the product and SC designs concurrently. By utilizing Mixed Integer Programming and a Genetic Algorithm, this research studies various research questions which examine modeling preferences and essential performance metrics, impacts of DEVELOPMENT OF A SIMULTANEOUS DESIGN FOR SUPPLY CHAIN PROCESS FOR THE OPTIMIZATION OF THE PRODUCT DESIGN AND SUPPLY CHAIN CONFIGURATION PROBLEMNuri Mehmet Gökhan, PhDUniversity of Pittsburgh, 2007 v using a sequential versus simultaneous design approach on these performance metrics, the robustness of the resulting SC design, and relative importance of the product and SC design on the profits. To answer these questions, different models are developed, tested with illustrative data, and the results are analyzed.The test results and industry experts' validations conclude that the developed DFSC models add significant value to the product design procedure resulting in a useful decision support tool. The results indicate that the simultaneous DFSC approach captures the complex interactions between the product and supply chain decisions, improving the overall profit of a product across its life cycle. Nora not only for their enthusiasm but also for all the coffee that kept me awake all the time. Keywords Mdem:Maximum potential demand over all periods (calculated by using maximum of timemultiplier t and lowest price t with υ t =1) INTRODUCTIONThis research focuses on understanding the impacts and proposed benefits of incorporating the supply chain configuration problem into the product design phase analogous to the Design for Manufacturability (DFM) concept introduced in the 1980s where manufacturing processes of a product are taken into account in the pr...

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Section: Solution Methodologiesmentioning

confidence: 99%

Development of a Simultaneous Design for Supply Chain Process for the Optimization of the Product Design and Supply Chain Configuration Problem

Gokhan¹

2010

Engineering Management Journal

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“…It is supposed to match customer demand that is, producing only enough to replenish what the customer has used or sold. Vergara et al (2002) have dealt the co ordination between different parts of simple supply chain. Materials should be moved from one supplier to other supplier as per the JIT.…”

Section: Supply Chain Systemmentioning

confidence: 99%

A state of art review on optimization techniques in just in time

Sultana¹,

Ahmed²

2014

10.5267/j.uscm

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With the development of faster means of communication, better quality computers and rapid transportation systems, manufacturing is no longer restricted at local level, but has become global in character. As a manufacturing company has to become competitive for its survival, it has to supply products of consistent high quality at reliable and reduced delivery time. Market also demands more product variants that means reduced lot size and high flexibility in operations. Manpower cost has also risen. All these factors tend to increase the product cost. However, the industry has to maintain the cost at a reasonable level. Confronting these challenges, companies worldwide are forced to find ways to reduce costs, improve quality, and meet the everchanging needs of their customers. One successful solution has been the adoption of Justintime (JIT) manufacturing strategy in which many functional areas of a company such as manufacturing, engineering, marketing, purchasing etc. are involved. In this paper, literature review on research works based on JIT was carried out and presented. The introductory section deals with the philosophy of JIT, and the concept involved in Kanban optimization and later this paper reviews literature on optimization Technique in JIT implementation.

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“…The genetic algorithms of simulation-based optimization models in the supply chain networks are supported through mathematical programming [101][102][103]. However, these studies mostly deal with strategic decisions, for instance combinatorial operation research problems such as multi-stage facility location, rather than tactical or operational ones.…”

Section: Integrated Simulation-based Optimization Modelsmentioning

confidence: 99%

Supply Chain Network Optimization of the Canadian Forest Products Industry: A Critical Review

Shahi¹,

Pulkki²

2013

AJIBM

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The Canadian forest products industry has failed to retain its competitiveness in the global markets because of the under-utilization of its resources. Supply chain optimization models can identify the best possible fibre utilization strategies from multiple options of value creation based on fluctuating market conditions in the forest industries. This paper comprehensively reviews the literature related to supply chain models used both in general and specifically in the forest products industry. The optimization models use information from multiple agents (market demand attributes, flexible wood procurement and manufacturing processes, and resource characteristics), and share this information at each level in the supply chain network. However, the modeling of two-way flow of information (market to forests and vice-versa) for order promising and demand fulfillment through all facilities including manufacturing, processing, raw material procurement and inventory control is missing. The studies that focus on optimization are mostly deterministic in nature and do not account for uncertainty both in supply of raw materials and demand of forest products. Simulation and optimization models have been independently used for supply chain management in the past. The literature lacks an integrated approach that combines simulation and optimization models throughout the supply chain network of the Canadian forest products industry. Further studies should focus on developing simulation-based optimization models that will help in providing an operational planning tool that meets industrial expectations and provides much better solutions than current industrial practice.

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An evolutionary algorithm for optimizing material flow in supply chains

Cited by 59 publications

References 10 publications

Development of a Simultaneous Design for Supply Chain Process for the Optimization of the Product Design and Supply Chain Configuration Problem

Development of a Simultaneous Design for Supply Chain Process for the Optimization of the Product Design and Supply Chain Configuration Problem

A state of art review on optimization techniques in just in time

Supply Chain Network Optimization of the Canadian Forest Products Industry: A Critical Review

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