Solving large unconstrainted multi level lot-sizing problem by a binary particle swarm optimization

2011 ◽  
Vol 6 (2) ◽  
pp. 133-140 ◽  
Author(s):  
Klorklear Wajanawichakon ◽  
Rapeepan Pitakaso
Keyword(s):  
Particle Swarm Optimization ◽  
Lot Sizing ◽  
Particle Swarm ◽  
Binary Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Lot Sizing Problem ◽  
Multi Level

Discrete Particle Swarm Optimization for the Multi-Level Lot-Sizing Problem

2012 ◽  
pp. 99-113
Author(s):  
Laurent Deroussi ◽  
David Lemoine
Keyword(s):  
Particle Swarm Optimization ◽  
Lot Sizing ◽  
Particle Swarm ◽  
Original Form ◽  
Discrete Particle Swarm Optimization ◽  
Swarm Optimization ◽  
Discrete Particle ◽  
Associated Production ◽  
Lot Sizing Problem ◽  
Multi Level

This paper presents a Discrete Particle Swarm Optimization (DPSO) approach for the Multi-Level Lot-Sizing Problem (MLLP), which is an uncapacitated lot sizing problem dedicated to materials requirements planning (MRP) systems. The proposed DPSO approach is based on cost modification and uses PSO in its original form with continuous velocity equations. Each particle of the swarm is represented by a matrix of logistic costs. A sequential approach heuristic, using Wagner-Whitin algorithm, is used to determine the associated production planning. The authors demonstrate that any solution of the MLLP can be reached by particles. The sequential heuristic is a subjective function from the particles space to the set of the production plans, which meet the customer’s demand. The authors test the DPSO Scheme on benchmarks found in literature, more specifically the unique DPSO that has been developed to solve the MLLP.

Discrete Particle Swarm Optimization for the Multi-Level Lot-Sizing Problem

2011 ◽  
Vol 2 (1) ◽  
pp. 44-57 ◽  
Author(s):  
Laurent Deroussi ◽  
David Lemoine
Keyword(s):  
Particle Swarm Optimization ◽  
Lot Sizing ◽  
Particle Swarm ◽  
Original Form ◽  
Discrete Particle Swarm Optimization ◽  
Sequential Approach ◽  
Swarm Optimization ◽  
Discrete Particle ◽  
Lot Sizing Problem ◽  
Multi Level

This paper presents a Discrete Particle Swarm Optimization (DPSO) approach for the Multi-Level Lot-Sizing Problem (MLLP), which is an uncapacitated lot sizing problem dedicated to materials requirements planning (MRP) systems. The proposed DPSO approach is based on cost modification and uses PSO in its original form with continuous velocity equations. Each particle of the swarm is represented by a matrix of logistic costs. A sequential approach heuristic, using Wagner-Whitin algorithm, is used to determine the associated production planning. The authors demonstrate that any solution of the MLLP can be reached by particles. The sequential heuristic is a subjective function from the particles space to the set of the production plans, which meet the customer’s demand. The authors test the DPSO Scheme on benchmarks found in literature, more specifically the unique DPSO that has been developed to solve the MLLP.

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