A fix and optimize method based approximate dynamic programming approach for the strategic fleet sizing and delivery planning problem

Logistics related costs constitute a major part in total cost of a product in general. Considering a company that delivers goods to its customers using its owned fleet, fleet ownership and operational costs together with the inventory costs compose the total logistics costs. In this study, we sugges...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Central European journal of operations research Ročník 33; číslo 1; s. 91 - 119
Hlavní autori: Aghazadeh, Duygu, Ertogral, Kadir
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2025
Springer Nature B.V
Predmet:
Algorithms
Business and Management
Composition
Customers
Distribution costs
Dynamic programming
Efficiency
Energy consumption
Heuristic
Inventory control
Logistics
Operating costs
Operations Research/Decision Theory
Optimization
Original Paper
Ownership
Pareto optimum
Planning
Replenishment
Suppliers
Supply chains
Vehicles
Approximate dynamic programming
Fix and optimize
Fleet sizing
Replenishment planning
ISSN:1435-246X, 1613-9178
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Logistics related costs constitute a major part in total cost of a product in general. Considering a company that delivers goods to its customers using its owned fleet, fleet ownership and operational costs together with the inventory costs compose the total logistics costs. In this study, we suggest an approximate Dynamic Programming algorithm, with a look ahead strategy, that uses the fix and optimize method as the imbedded heuristic for solving integrated fleet composition and replenishment planning problem. The total annual distribution cost factors considered in the problem are vehicle ownership costs, approximate routing costs, and inventory related costs. In this problem, we aim to minimize the total logistic cost by optimizing the fleet composition, replenishment patterns, and customers assigned to each vehicle in the fleet. We produced a set of reasonably large instances randomly and showed the efficacy of the suggested solution method.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1435-246X
1613-9178
DOI:10.1007/s10100-024-00911-6