Combining Fix and Relax Heuristic and LP-Metric Method to Solve the Multi-Objective Integrated Production-Routing Problem

2022 ◽  
pp. 244-265
Author(s):  
Besma Zeddam ◽  
Fayçal Belkaid ◽  
Mohammed Bennekrouf
Keyword(s):  
Computational Results ◽  
Rolling Horizon ◽  
Routing Problem ◽  
Integrated Production ◽  
Reasonable Time ◽  
System A ◽  
Production Inventory ◽  
Objective Model ◽  
Lp Metric ◽  
Production Routing

Production routing problem is one of the problems of the integrated planning that interests in optimizing simultaneously production, inventory, and distribution planning. This chapter has the purpose of developing two mono-objective models for the production-routing problem: one of them minimizes the total costs which is the classical objective while the other one minimizes the energy consumed by the production system. A bi-objective model is then proposed to combine the two objectives mentioned previously using LP-metric method. To solve big instances of the problem in reasonable time, an approximate approach is proposed using the rolling horizon-based fix and relax heuristic. Finally, computational results are presented to compare the solutions obtained by both approaches.

On the integrated production, inventory, and distribution routing problem

2006 ◽  
Vol 38 (11) ◽  
pp. 955-970 ◽  
Author(s):  
Lei Lei ◽  
Shuguang Liu ◽  
Andrzej Ruszczynski ◽  
Sunju Park
Keyword(s):  
Routing Problem ◽  
Integrated Production ◽  
Production Inventory

scholarly journals A Memetic Algorithm for an External Depot Production Routing Problem

Algorithms ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 27
Author(s):  
Bi Kouaï Bertin Kayé ◽  
Moustapha Diaby ◽  
Moussa Koivogui ◽  
Souleymane Oumtanaga
Keyword(s):  
Supply Chain ◽  
Local Search ◽  
Memetic Algorithm ◽  
Mutation Operator ◽  
Phase Decomposition ◽  
Local Search Algorithms ◽  
Two Phase ◽  
Routing Problem ◽  
Production Inventory ◽  
Production Routing

This study aims to compare the results of a memetic algorithm with those of the two-phase decomposition heuristic on the external depot production routing problem in a supply chain. We have modified the classical scheme of a genetic algorithm by replacing the mutation operator by three local search algorithms. The first local search consists in exchanging two customers visited the same day. The second consists in trying an exchange between two customers visited at consecutive periods and the third consists in removing a customer from his current tour for a better insertion in any tour of the same period. The tests that were carried out on 128 instances of the literature have highlighted the effectiveness of the memetic algorithm developed in this work compared to the two-phase decomposition heuristic. This is reflected by the fact that the results obtained by the memetic algorithm lead to a reduction in the overall average cost of production, inventory, and transport, ranging from 3.65% to 16.73% with an overall rate of 11.07% with regard to the results obtained with the two-phase decomposition heuristic. The outcomes will be beneficial to researchers and supply chain managers in the choice and development of heuristics and metaheuristics for the resolution of production routing problem.

An Efficient Approach for Solving Integrated Production and Distribution Planning Problems

2020 ◽  
Vol 10 (2) ◽  
pp. 25-44
Author(s):  
Besma Zeddam ◽  
Fayçal Belkaid ◽  
Mohammed Bennekrouf
Keyword(s):  
Supply Chain ◽  
Research Field ◽  
Sustainable Supply Chain ◽  
Integrated Planning ◽  
Routing Problem ◽  
Distribution Planning ◽  
Production And Distribution ◽  
Production And Distribution Planning ◽  
Lp Metric ◽  
Production Routing

The increasing customer expectations for customized products of high quality in short delays and the worldwide competition in terms of quality and costs have pushed industries to implement new strategies to manage their supply chain decisions. In this context, the integrated planning is becoming the most dominant over the operational research field because of its efficiency and its ability to cover the different aspects of the problem. Production routing problem is one of the problems of the integrated planning that is of interest in optimizing simultaneously production, inventory, and distribution planning. This paper has the purpose of developing two mono-objective models for the production-routing problem; one of them minimizes the total costs, while the other one minimizes the energy consumed by the production system. Finally, a bi-objective model is proposed to combine the two objectives mentioned previously using the LP-metric method in the context of a sustainable supply chain. Experimental results are also presented and discussed through the different scenarios.

scholarly journals An integrated production inventory routing problem for multi perishable products with fuzzy demands and time windows

2019 ◽  
Vol 52 (13) ◽  
pp. 523-528 ◽  
Author(s):  
A. Ghasemkhani ◽  
R. Tavakkoli-Moghaddam ◽  
S. Shahnejat-Bushehri ◽  
S. Momen ◽  
H. Tavakkoli-Moghaddam
Keyword(s):  
Time Windows ◽  
Perishable Products ◽  
Inventory Routing ◽  
Routing Problem ◽  
Integrated Production ◽  
Inventory Routing Problem ◽  
Production Inventory

scholarly journals Three-Phase Methodology Incorporating Scatter Search for Integrated Production, Inventory, and Distribution Routing Problem

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Noor Hasnah Moin ◽  
Titi Yuliana
Keyword(s):  
Scatter Search ◽  
Planning Horizon ◽  
Benchmark Problems ◽  
Production Plant ◽  
Routing Problem ◽  
Integrated Production ◽  
Geographically Dispersed ◽  
Three Phase ◽  
Production Inventory ◽  
Single Production

This paper proposes the use of scatter search metaheuristic to solve an integrated production, inventory, and distribution routing problem. The problem is based on a single production plant that produces a single product that is delivered toNgeographically dispersed customers by a set of homogenous fleet of vehicles. The objective is to construct a production plan and delivery schedule to minimize the total costs and ensuring each customer’s demand is met over the planning horizon. We assumed that excess production can be stored at the plant or at customer’s sites within some limits, but stockouts due to backordering or backlogging are not allowed. Further testing on a set of benchmark problems to assess the effectiveness of our method is also carried out. We compare our results to the existing metaheuristic algorithms proposed in the literature.

Sign in / Sign up

Export Citation Format

Share Document