Deterministic Dynamic Multi-Stage Uncapacitated Lot-Sizing Problems

1993 ◽  
pp. 382-391
Author(s):  
Wolfgang Domschke ◽  
Birgit Schildt
Keyword(s):  
Lot Sizing ◽  
Multi Stage ◽  
Deterministic Dynamic

Multi-stage lot sizing in a serial production system

1986 ◽  
Vol 24 (3) ◽  
pp. 517-534 ◽  
Author(s):  
SHAWNEE K. VICKERY ◽  
ROBERT E. MARKLAND
Keyword(s):  
Production System ◽  
Lot Sizing ◽  
Serial Production ◽  
Multi Stage

Echelon stock formulation for multi-stage lot-sizing with component lead times

1993 ◽  
Vol 24 (9) ◽  
pp. 1759-1775 ◽  
Author(s):  
ALISTAIR R. CLARK ◽  
VINICIUS A. ARMENTANO
Keyword(s):  
Lot Sizing ◽  
Lead Times ◽  
Multi Stage

A heuristic method for lot-sizing in multi-stage systems

1997 ◽  
Vol 24 (9) ◽  
pp. 861-874 ◽  
Author(s):  
Paulo M. França ◽  
Vinícius A. Armentano ◽  
Regina E. Berretta ◽  
Alistair R. Clark
Keyword(s):  
Lot Sizing ◽  
Heuristic Method ◽  
Multi Stage

scholarly journals A multistage stochastic lot-sizing problem with cancellation and postponement under uncertain demands

2021 ◽  
Author(s):  
Carlos E Testuri ◽  
Héctor Cancela ◽  
Víctor M. Albornoz
Keyword(s):  
Information Structure ◽  
Lot Sizing ◽  
Valid Inequalities ◽  
Mixed Integer ◽  
Uncertain Demand ◽  
Programming Approach ◽  
Lead Times ◽  
Multi Stage ◽  
Lot Sizing Problem ◽  
Capacitated Lot Sizing

A multistage stochastic capacitated discrete procurement problem with lead times, cancellation and postponement is addressed.  The problem determines the procurement of a product under uncertain demand at minimal expected cost during a time horizon.  The supply of the product is made through the purchase of optional distinguishable orders of fixed size with delivery time.  Due to the unveiling of uncertainty over time it is possible to make cancellation and postponement corrective decisions on order procurement.  These decisions involve costs and times of implementation.  A model of the problem is formulated as an extension of a discrete capacitated lot-sizing problem under uncertain demand and lead times through a multi-stage stochastic mixed-integer linear programming approach.  Valid inequalities are generated, based on a conventional inequalities approach, to tighten the model formulation.  Experiments are performed for several problem instances with different uncertainty information structure.  Their results allow to conclude that the incorporation of a subset of the generated inequalities favor the model solution.

scholarly journals Capacity coordination in hybrid make-to-stock/make-to-order contexts using an enhanced multi-stage model

2017 ◽  
Vol 14 (3) ◽  
pp. 396
Author(s):  
Masoud Rabbani ◽  
Sara Motevali Haghighi ◽  
Hamed Farrokhi-Asl ◽  
Neda Manavizadeh
Keyword(s):  
Capacity Planning ◽  
Production Systems ◽  
Lot Sizing ◽  
Service Level ◽  
Stage Model ◽  
Order Acceptance ◽  
Industrial Case Study ◽  
Make To Order ◽  
Multi Stage ◽  
Make To Stock

One of the most attracting production systems that has recently been vastly explored by practitioners and academicians is hybrid make-to-stock/make-to-order. Having a hierarchical production planning structure considered, this paper develops a multi-stage model to cope with the operational decisions, including order acceptance/rejection, product lot sizing, overtime capacity planning, outsourcing, and due date setting. Moreover, the proposed framework also comprises providing alternative products for the coming orders in order to enhance service level of the firm to the customers. In order to validate the presented framework, it is applied in a real industrial case study and the obtained results approve validity of the proposed framework. 

scholarly journals A Multi-Stage Stochastic Programming Model for the Multi-Echelon Multi-Period Reverse Logistics Problem

2021 ◽  
Vol 13 (24) ◽  
pp. 13596
Author(s):  
Vahid Azizi ◽  
Guiping Hu
Keyword(s):  
Reverse Logistics ◽  
Programming Model ◽  
Lot Sizing ◽  
Continuous Distribution ◽  
Optimal Solution ◽  
Forward Selection ◽  
Multi Stage ◽  
Stochastic Parameters ◽  
Stochastic Solution ◽  
Stochastic Programming Model

Reverse logistics planning plays a crucial role in supply chain management. Stochasticity in different parameters along with time horizon can be a challenge in solving reverse logistics problems. This paper proposes a multi-stage, multi-period reverse logistics with lot sizing decisions under uncertainties. The main uncertain factors are return and demand quantities, and return quality. Moment matching method was adopted to generate a discrete set of scenarios to represent the original continuous distribution of stochastic parameters. Fast forward selection algorithm was employed to select the most representative scenarios and facilitate computational tractability. A case study was conducted and optimal solution of the recursive problem obtained by solving extensive form. Sensitivity analysis was implemented on different elements of stochastic solution. Results sow that solution of recursive problem (RP) outperforms the solution obtained from the problem with expected values of uncertain parameters (EEV).

The application of valid inequalities to the multi-stage lot-sizing problem

1995 ◽  
Vol 22 (7) ◽  
pp. 669-680 ◽  
Author(s):  
Alistair Richard Clark ◽  
Vinicius Amaral Armentano
Keyword(s):  
Lot Sizing ◽  
Valid Inequalities ◽  
Multi Stage ◽  
Lot Sizing Problem
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