1,499 research outputs found
Product Return Handling
In this article we focus on product return handling and warehousingissues. In some businesses return rates can be well over 20% andreturns can be especially costly when not handled properly. In spiteof this, many managers have handled returns extemporarily. The factthat quantitative methods barely exist to support return handlingdecisions adds to this. In this article we bridge those issues by 1)going over the key decisions related with return handling; 2)identifying quantitative models to support those decisions.Furthermore, we provide insights on directions for future research.reverse logistics;decision-making;quantitative models;retailing and warehousing
The impact of freight transport capacity limitations on supply chain dynamics
We investigate how capacity limitations in the transportation system affect the dynamic behaviour of supply chains. We are interested in the more recently defined, 'backlash' effect. Using a system dynamics simulation approach, we replicate the well-known Beer Game supply chain for different transport capacity management scenarios. The results indicate that transport capacity limitations negatively impact on inventory and backlog costs, although there is a positive impact on the 'backlash' effect. We show that it is possible for both backlog and inventory to simultaneous occur, a situation which does not arise with the uncapacitated scenario. A vertical collaborative approach to transport provision is able to overcome such a trade-off. © 2013 Taylor & Francis
Design and Control of Warehouse Order Picking: a literature review
Order picking has long been identified as the most labour-intensive and costly activity for almost every warehouse; the cost of order picking is estimated to be as much as 55% of the total warehouse operating expense. Any underperformance in order picking can lead to unsatisfactory service and high operational cost for its warehouse, and consequently for the whole supply chain. In order to operate efficiently, the orderpicking process needs to be robustly designed and optimally controlled. This paper gives a literature overview on typical decision problems in design and control of manual order-picking processes. We focus on optimal (internal) layout design, storage assignment methods, routing methods, order batching and zoning. The research in this area has grown rapidly recently. Still, combinations of the above areas have hardly been explored. Order-picking system developments in practice lead to promising new research directions.Order picking;Logistics;Warehouse Management
High-Level Object Oriented Genetic Programming in Logistic Warehouse Optimization
DisertaÄnĂ prĂĄce je zamÄĆena na optimalizaci prĆŻbÄhu pracovnĂch operacĂ v logistickĂœch skladech a distribuÄnĂch centrech. HlavnĂm cĂlem je optimalizovat procesy plĂĄnovĂĄnĂ, rozvrhovĂĄnĂ a odbavovĂĄnĂ. JelikoĆŸ jde o problĂ©m patĆĂcĂ do tĆĂdy sloĆŸitosti NP-teĆŸkĂœ, je vĂœpoÄetnÄ velmi nĂĄroÄnĂ© nalĂ©zt optimĂĄlnĂ ĆeĆĄenĂ. MotivacĂ pro ĆeĆĄenĂ tĂ©to prĂĄce je vyplnÄnĂ pomyslnĂ© mezery mezi metodami zkoumanĂœmi na vÄdeckĂ© a akademickĂ© pĆŻdÄ a metodami pouĆŸĂvanĂœmi v produkÄnĂch komerÄnĂch prostĆedĂch. JĂĄdro optimalizaÄnĂho algoritmu je zaloĆŸeno na zĂĄkladÄ genetickĂ©ho programovĂĄnĂ ĆĂzenĂ©ho bezkontextovou gramatikou. HlavnĂm pĆĂnosem tĂ©to prĂĄce je a) navrhnout novĂœ optimalizaÄnĂ algoritmus, kterĂœ respektuje nĂĄsledujĂcĂ optimalizaÄnĂ podmĂnky: celkovĂœ Äas zpracovĂĄnĂ, vyuĆŸitĂ zdrojĆŻ, a zahlcenĂ skladovĂœch uliÄek, kterĂ© mĆŻĆŸe nastat bÄhem zpracovĂĄnĂ ĂșkolĆŻ, b) analyzovat historickĂĄ data z provozu skladu a vyvinout sadu testovacĂch pĆĂkladĆŻ, kterĂ© mohou slouĆŸit jako referenÄnĂ vĂœsledky pro dalĆĄĂ vĂœzkum, a dĂĄle c) pokusit se pĆedÄit stanovenĂ© referenÄnĂ vĂœsledky dosaĆŸenĂ© kvalifikovanĂœm a trĂ©novanĂœm operaÄnĂm manaĆŸerem jednoho z nejvÄtĆĄĂch skladĆŻ ve stĆednĂ EvropÄ.This work is focused on the work-flow optimization in logistic warehouses and distribution centers. The main aim is to optimize process planning, scheduling, and dispatching. The problem is quite accented in recent years. The problem is of NP hard class of problems and where is very computationally demanding to find an optimal solution. The main motivation for solving this problem is to fill the gap between the new optimization methods developed by researchers in academic world and the methods used in business world. The core of the optimization algorithm is built on the genetic programming driven by the context-free grammar. The main contribution of the thesis is a) to propose a new optimization algorithm which respects the makespan, the utilization, and the congestions of aisles which may occur, b) to analyze historical operational data from warehouse and to develop the set of benchmarks which could serve as the reference baseline results for further research, and c) to try outperform the baseline results set by the skilled and trained operational manager of the one of the biggest warehouses in the middle Europe.
An Innovative of Simul Model for Ready-Mix Concretes in The Concept of Third Party Logistics and Supply Chain Management in Malaysia and Thailand
The research discusses on issues in an order fulfilment for sustainable ready-mix concrete as desired for an eco-friendly choice of integration in the concept of third-party logistics and supply chain management. There are insufficient and inappropriate means in concrete industry which has contributed to un-environmentally friendly especially in Malaysia and Thailand. The supply management and logistics are the factors in designing of product which influence on the environmental, safety and health. It also involves on costs of energy, effectiveness, economic certainty, businesses and other related issues. Through the current practices with relevant factors, the analysis of model is no longer realistic. The sustainable of simulation in logistics model should relate to descriptive approaches. Through the less numbers of movements and reduction on carbon dioxide are significant for the simulation. In some developing countries, the involvements of commercial players and government bodies have their responsibility in controlling, simulating economic and business development. Relation to this fundamental deficiency, this paper utilized SIMUL model in the logistics for sustainable ready mixed concrete, eco-friendly and to meet on the order fulfilments. The result clearly indicates that the eco-friendly SIMUL model can be more sustainable, cost efficient and time effective in fulfilling orders for the operational of ready-mix concrete in future
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Decision support for build-to-order supply chain management through multiobjective optimization
This paper aims to identify the gaps in decision-making support based on
multiobjective optimization for build-to-order supply chain management (BTOSCM).
To this end, it reviews the literature available on modelling build-to-order
supply chains (BTO-SC) with the focus on adopting multiobjective optimization
(MOO) techniques as a decision support tool. The literature has been classified based
on the nature of the decisions in different part of the supply chain, and the key
decision areas across a typical BTO-SC are discussed in detail. Available software
packages suitable for supporting decision making in BTO supply chains are also
identified and their related solutions are outlined. The gap between the modelling and
optimization techniques developed in the literature and the decision support needed in
practice are highlighted and future research directions to better exploit the decision
support capabilities of MOO are proposed
Decision support for build-to-order supply chain management through multiobjective optimization
This is the post-print version of the final paper published in International Journal of Production Economics. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.This paper aims to identify the gaps in decision-making support based on multiobjective optimization (MOO) for build-to-order supply chain management (BTO-SCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting MOO techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted. Future research directions to better exploit the decision support capabilities of MOO are proposed. These include: reformulation of the extant optimization models with a MOO perspective, development of decision supports for interfaces not involving manufacturers, development of scenarios around service-based objectives, development of efficient solution tools, considering the interests of each supply chain party as a separate objective to account for fair treatment of their requirements, and applying the existing methodologies on real-life data sets.Brunel Research Initiative and Enterprise Fund (BRIEF
Product Return Handling
In this article we focus on product return handling and warehousing
issues. In some businesses return rates can be well over 20% and
returns can be especially costly when not handled properly. In spite
of this, many managers have handled returns extemporarily. The fact
that quantitative methods barely exist to support return handling
decisions adds to this. In this article we bridge those issues by 1)
going over the key decisions related with return handling; 2)
identifying quantitative models to support those decisions.
Furthermore, we provide insights on directions for future research
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