scholarly journals A Location-Inventory-Routing Problem in Forward and Reverse Logistics Network Design

2016 ◽  
Vol 2016 ◽  
pp. 1-18 ◽  
Author(s):  
Qunli Yuchi ◽  
Zhengwen He ◽  
Zhen Yang ◽  
Nengmin Wang
Keyword(s):  
Network Design ◽  
Programming Model ◽  
Optimal Solution ◽  
Nonlinear Integer Programming ◽  
Inventory Routing ◽  
Distribution Centers ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Reverse Logistic

We study a new problem of location-inventory-routing in forward and reverse logistic (LIRP-FRL) network design, which simultaneously integrates the location decisions of distribution centers (DCs), the inventory policies of opened DCs, and the vehicle routing decision in serving customers, in which new goods are produced and damaged goods are repaired by a manufacturer and then returned to the market to satisfy customers’ demands as new ones. Our objective is to minimize the total costs of manufacturing and remanufacturing goods, building DCs, shipping goods (new or recovered) between the manufacturer and opened DCs, and distributing new or recovered goods to customers and ordering and storage costs of goods. A nonlinear integer programming model is proposed to formulate the LIRP-FRL. A new tabu search (NTS) algorithm is developed to achieve near optimal solution of the problem. Numerical experiments on the benchmark instances of a simplified version of the LIRP-FRL, the capacitated location routing problem, and the randomly generated LIRP-FRL instances demonstrate the effectiveness and efficiency of the proposed NTS algorithm in problem resolution.

scholarly journals Location Routing Problem with Consideration of CO2 Emissions Cost: A Case Study

2020 ◽  
Vol 21 (2) ◽  
pp. 225-234
Author(s):  
Ananda Noor Sholichah ◽  
Y Yuniaristanto ◽  
I Wayan Suletra
Keyword(s):  
Co2 Emissions ◽  
Time Windows ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Distribution Centers ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Study Results

Location and routing are the main critical problems investigated in a logistic. Location-Routing Problem (LRP) involves determining the location of facilities and vehicle routes to supply customer's demands. Determination of depots as distribution centers is one of the problems in LRP.  In LRP, carbon emissions need to be considered because these problems cause global warming and climate change. In this paper, a new mathematical model for LRP considering CO2 emissions minimization is proposed. This study developed a new  Mixed Integer Linear Programming (MILP)  model for LRP with time windows and considered the environmental impacts.  Finally, a case study was conducted in the province of Central Java, Indonesia. In this case study, there are three depot candidates. The study results indicated that using this method in existing conditions and constraints provides a more optimal solution than the company's actual route. A sensitivity analysis was also carried out in this case study.

scholarly journals The inventory replenishment policy in an uncertain production-inventory-routing system

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Chenyin Wang ◽  
Yaodong Ni ◽  
Xiangfeng Yang
Keyword(s):  
Programming Model ◽  
Optimal Solution ◽  
Maximum Level ◽  
Equivalent Model ◽  
Uncertain Programming ◽  
Inventory Routing ◽  
Routing Problem ◽  
Uncertain Variables ◽  
Confidence Levels ◽  
Production Inventory

<p style='text-indent:20px;'>This study introduces an uncertain programming model for the integrated production routing problem (PRP) in an uncertain production-inventory-routing system. Based on uncertainty theory, an uncertain programming model is proposed firstly and then transformed into a deterministic and equivalent model. The study further probes into different types of replenishment policies under the condition of uncertain demands, mainly the uncertain maximum level (UML) policy and the uncertain order-up to level (UOU) policy. Some inequalities are put forward to define the UML policy and the UOU policy under the uncertain environments, and the influences brought by uncertain demands are highlighted. The overall costs with optimal solution of the uncertain decision model grow with the increase of the confidence levels. And they are simultaneously affected by the variances of uncertain variables but rely on the value of confidence levels. Results show that when the confidence levels are not less than 0.5, the cost difference between the two policies begins to narrow along with the increase of the confidence levels and the variances of uncertain variables, eventually being trending to zero. When there are higher confidence levels and relatively large uncertainty in realistic applications, in which the solution scale is escalated, being conducive to its efficiency advantage, the comprehensive advantages of the UOU policy is obvious.</p>

scholarly journals A Bi-Level Programming Approach to the Location-Routing Problem with Cargo Splitting under Low-Carbon Policies

Mathematics ◽  
2021 ◽  
Vol 9 (18) ◽  
pp. 2325
Author(s):  
Cong Wang ◽  
Zhongxiu Peng ◽  
Xijun Xu
Keyword(s):  
Decision Making ◽  
Decision Maker ◽  
Programming Model ◽  
Programming Approach ◽  
Low Carbon ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Level Model ◽  
The Impact

To identify the impact of low-carbon policies on the location-routing problem (LRP) with cargo splitting (LRPCS), this paper first constructs the bi-level programming model of LRPCS. On this basis, the bi-level programming models of LRPCS under four low-carbon policies are constructed, respectively. The upper-level model takes the engineering construction department as the decision-maker to decide on the distribution center’s location. The lower-level model takes the logistics and distribution department as the decision-maker to make decisions on the vehicle distribution route’s scheme. Secondly, the hybrid algorithm of Ant Colony Optimization and Tabu Search (ACO-TS) is designed, and an example is introduced to verify the model’s and algorithm’s effectiveness. Finally, multiple sets of experiments are designed to explore the impact of various low-carbon policies on the decision-making of the LRPCS. The experimental results show that the influence of the carbon tax policy is the greatest, the carbon trading and carbon offset policy have a certain impact on the decision-making of the LRPCS, and the influence of the emission cap policy is the least. Based on this, we provide the relevant low-carbon policies advice and management implications.

scholarly journals Formulation and a heuristic approach for the Orienteering Location-Routing Problem

2020 ◽  
Author(s):  
Ali Nadizadeh
Keyword(s):  
Programming Model ◽  
Standard Test ◽  
Test Problems ◽  
Military Operations ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Practical Applications ◽  
Location Routing ◽  
Commercial Solver ◽  
Short Time

In this paper, a new version of the location-routing problem (LRP), named orienteering location-routing problem (OLRP) is investigated. The problem is composed of two-well known problems: team orienteering problem (TOP) and LRP. There are some challenging practical applications in logistics, tourism, military operations, and other fields, which can be modeled by OLRP. The problem is to consider the location and routing with a special objective function . In the OLRP, a set of nodes with specific scores is given, and some stations among candidate stations should be established. Moreover, there are some routes limited in length, which start from a station, visit some nodes and then return to the same station. Maximizing the sum of the collected scores is the goal of OLRP. To model the problem, an integer linear programming model is proposed. Against a commercial solver, a heuristic GRASP is developed for solving the standard test problems. Most test problems are found difficult to solve optimally with commercial software while the GRASP can find the best known or close to the best-known solution in a short time .

scholarly journals Optimization of Base Location and Patrol Routes for Unmanned Aerial Vehicles in Border Intelligence, Surveillance and Reconnaissance

2018 ◽  
Author(s):  
Yao Liu ◽  
Zhong Liu ◽  
Jianmai Shi ◽  
Guohua Wu ◽  
Chao Chen
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Heuristic Algorithms ◽  
Programming Model ◽  
Base Station ◽  
Base Stations ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Solution Approach ◽  
Location Routing ◽  
Aerial Vehicles

The location routing problem of unmanned aerial vehicles (UAV) in border patrol for intelligence, surveillance and reconnaissance is investigated, where the location of UAV base stations and the UAV flying routes for visiting the targets in border area are jointly optimized. The capacity of the base station and the endurance of the UAV are considered. A binary integer programming model is developed to formulate the problem, and two heuristic algorithms combined with local search strategies are designed for solving the problem. The experiment design for simulating the distribution of stations and targets in border is proposed for generating random test instances. Also, an example based on the Sino-Vietnamese border is presented to illustrate the problem and the solution approach. The performance of the two algorithms are analyzed and compared through randomly generated instances.

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