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See detailGeneral lotsizing in a closed-loop supply chain with uncertain returns
Amand, Guillaume ULg; Arda, Yasemin ULg

Conference (2013, July 03)

We consider a multi-product capacitated lotsizing and scheduling prob- lem with sequence-dependent setups and stochastic product returns. The returned products accumulate in an input inventory and can be ... [more ▼]

We consider a multi-product capacitated lotsizing and scheduling prob- lem with sequence-dependent setups and stochastic product returns. The returned products accumulate in an input inventory and can be sold as new items after a remanufacturing process. The determinis- tic demand of end items can also be satisfied through a manufacturing process that is fed by an unlimited source of raw materials. An ap- proximate dynamic algorithm is developed to solve both single-item and multi-items cases. [less ▲]

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See detailA general lot-sizing problem in a closed-loop supply chain with returns
Amand, Guillaume ULg; Arda, Yasemin ULg

Conference (2013, February 08)

We consider a stochastic version of the multi-product multi-level capacitated lotsizing and scheduling problem with sequence-dependent setups. A bottler needs to determine its production schedule over a ... [more ▼]

We consider a stochastic version of the multi-product multi-level capacitated lotsizing and scheduling problem with sequence-dependent setups. A bottler needs to determine its production schedule over a finite horizon in order to satisfy a deterministic demand. The raw materials are supplied through two different sources: uncapacitated reserves of new bottles and the uncertain returns of used bottles. We present results for the single-item case. [less ▲]

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See detailA capacity game in transportation management
Amand, Guillaume ULg; Arda, Yasemin ULg

E-print/Working paper (2012)

Detailed reference viewed: 32 (16 ULg)
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See detailA capacity game in transportation management
Amand, Guillaume ULg; Arda, Yasemin ULg

Conference (2011, July 10)

This study analyzes the contractual relation between a retailer and a carrier with the aim of determining possible deviations from the optimal system performance. In order to face a random demand, the ... [more ▼]

This study analyzes the contractual relation between a retailer and a carrier with the aim of determining possible deviations from the optimal system performance. In order to face a random demand, the retailer submits a contract to the carrier based on the number of units transported and on the number of truck used. Then, before uncertainty is resolved, the carrier decides of the number of trucks that he reserves. Once the demand is known, the carrier may also request additional trucks at a higher cost. The result shows that the proposed contract does not coordinate the supply chain. [less ▲]

Detailed reference viewed: 25 (11 ULg)
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See detailMultiperiod vehicle loading optimization with stochastic supply
Amand, Guillaume ULg; Arda, Yasemin ULg; Crama, Yves ULg et al

Scientific conference (2011, April 07)

Detailed reference viewed: 16 (6 ULg)
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See detailA capacity game in transportation management
Amand, Guillaume ULg; Arda, Yasemin ULg

Conference (2011, March 03)

Emerging concerns about competitiveness induce a growing number of firms to outsource their outbound transportation operations to third-party logistics providers. The resulting increase in the number of ... [more ▼]

Emerging concerns about competitiveness induce a growing number of firms to outsource their outbound transportation operations to third-party logistics providers. The resulting increase in the number of actors often leads to sub-optimal supply chain actions due to the antagonistic nature of the economic objectives of the partners. With the aim of determining possible deviations from the optimal system performance in such supply chains, this study analyzes the contractual relation between a retailer and a third-party logistics provider (carrier) using game theoretical approaches. The partners of the studied supply chain play a Stackelberg game in which the retailer is the leader and the carrier is the follower. The retailer faces an uncertain demand and needs to supply his store from his warehouse. he has the option of not meeting all the demand but must satisfy at least a minimum proportion of the fi nall demand. On the other hand, the carrier has to determine the number of trucks needed to satisfy this demand before uncertainty is resolved. Once demand is realized, if the reserved transportation capacity is insufficient, the carrier also has the possibility to requisition trucks at a higher price. We modelise the problem and propose a contract having two parameters : the quantity of transported items and the number of truck used. In our settings, the retailer is the one that submits the contract and the carrier decides if he accepts it or not. We compare this situation with a centralized model where a single decision maker takes all the decisions. [less ▲]

Detailed reference viewed: 75 (27 ULg)
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See detailVehicle loading optimization with stochastic supply
Amand, Guillaume ULg; Arda, Yasemin ULg; Crama, Yves ULg et al

Conference (2010, January 29)

Detailed reference viewed: 19 (5 ULg)
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See detailA capacity game in transportation planning
Amand, Guillaume ULg; Arda, Yasemin ULg

Conference (2010, January 28)

Emerging concerns about competitiveness induce a growing number of firms to outsource their outbound transportation operations to third-party logistics providers. The resulting increase in the number of ... [more ▼]

Emerging concerns about competitiveness induce a growing number of firms to outsource their outbound transportation operations to third-party logistics providers. The resulting increase in the number of actors often leads to sub-optimal supply chain actions due to the antagonistic nature of the economic objectives of the partners. With the aim of determining possible deviations from the optimal system performance in such supply chains, this study analyzes the contractual relation between a retailer and a third-party logistics provider (carrier) using game theoretical approaches. The partners of the studied supply chain play a Stackelberg game in which the retailer is the leader and the carrier is the follower. The retailer faces an uncertain demand and needs to supply his store from his warehouse. he has the option of not meeting all the demand but must satisfy at least a minimum proportion of the fi nall demand. On the other hand, the carrier has to determine the number of trucks needed to satisfy this demand before uncertainty is resolved. Once demand is realized, if the reserved transportation capacity is insufficient, the carrier also has the possibility to requisition trucks at a higher price. We modelise the problem and propose a contract having two parameters : the quantity of transported items and the number of truck used. In our settings, the retailer is the one that submits the contract and the carrier decides if he accepts it or not. We compare this situation with a centralized model where a single decision maker takes all the decisions. [less ▲]

Detailed reference viewed: 22 (11 ULg)
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See detailVehicle loading optimization with stochastic supply
Amand, Guillaume ULg; Arda, Yasemin ULg; Crama, Yves ULg et al

Conference (2009, July 07)

The increased availability of information makes it possible to coordinate processes which are usually functionnally separated in large companies, such as production and transportation. This work ... [more ▼]

The increased availability of information makes it possible to coordinate processes which are usually functionnally separated in large companies, such as production and transportation. This work investigates the optimization of vehicle loading for individual orders over a multiperiod horizon when items have stochastic release dates from production, and time windows are imposed for delivery at the customer plant. The loading decisions are made in order to minimize the expected cost. Starting from the deterministic model, we develop scenario-based models for the stochastic version of the problem and we investigate the performance of various solution methods. [less ▲]

Detailed reference viewed: 26 (9 ULg)