Bi-level programming model for post-disaster emergency supplies scheduling with time windows and its algorithm

2022 ◽  
Vol 16 (1) ◽  
pp. 45
Author(s):  
Fuyu Wang ◽  
Yan Li ◽  
Yan Li ◽  
Jingjing Chen
Keyword(s):  
Programming Model ◽  
Time Windows ◽  
Post Disaster

scholarly journals New general mixed-integer linear programming model for mobile workforce management

2021 ◽  
Author(s):  
András Éles ◽  
István Heckl ◽  
Heriberto Cabezas
Keyword(s):  
Programming Model ◽  
Time Windows ◽  
Mutual Exclusion ◽  
Parallel Execution ◽  
Mixed Integer ◽  
Management Problem ◽  
Routing Problem ◽  
Workforce Management ◽  
Computational Performance ◽  
Wide Range

AbstractA mathematical model is introduced to solve a mobile workforce management problem. In such a problem there are a number of tasks to be executed at different locations by various teams. For example, when an electricity utility company has to deal with planned system upgrades and damages caused by storms. The aim is to determine the schedule of the teams in such a way that the overall cost is minimal. The mobile workforce management problem involves scheduling. The following questions should be answered: when to perform a task, how to route vehicles—the vehicle routing problem—and the order the sites should be visited and by which teams. These problems are already complex in themselves. This paper proposes an integrated mathematical programming model formulation, which, by the assignment of its binary variables, can be easily included in heuristic algorithmic frameworks. In the problem specification, a wide range of parameters can be set. This includes absolute and expected time windows for tasks, packing and unpacking in case of team movement, resource utilization, relations between tasks such as precedence, mutual exclusion or parallel execution, and team-dependent travelling and execution times and costs. To make the model able to solve larger problems, an algorithmic framework is also implemented which can be used to find heuristic solutions in acceptable time. This latter solution method can be used as an alternative. Computational performance is examined through a series of test cases in which the most important factors are scaled.

scholarly journals Integrated Harvest and Farm-to-Door Distribution Scheduling with Postharvest Quality Deterioration for Vegetable Online Retailing

Agronomy ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 724
Author(s):  
Yiping Jiang ◽  
Bei Bian ◽  
Lingling Li
Keyword(s):  
Genetic Algorithm ◽  
Numerical Experiments ◽  
Programming Model ◽  
Time Windows ◽  
Sensitivity Analyses ◽  
Postharvest Quality ◽  
Online Retailing ◽  
Quality Deterioration ◽  
Distribution Scheduling ◽  
Proposed Model

With the rise of vegetable online retailing in recent years, the fulfillment of vegetable online orders has been receiving more and more attention. This paper addresses an integrated optimization model for harvest and farm-to-door distribution scheduling for vegetable online retailing. Firstly, we capture the perishable property of vegetables, and model it as a quadratic postharvest quality deterioration function. Then, we incorporate the postharvest quality deterioration function into the integrated harvest and farm-to-door distribution scheduling and formulate it as a quadratic vehicle routing programming model with time windows. Next, we propose a genetic algorithm with adaptive operators (GAAO) to solve the model. Finally, we carry out numerical experiments to verify the performance of the proposed model and algorithm, and report the results of numerical experiments and sensitivity analyses.

A mixed procurement model for humanitarian relief chains

2019 ◽  
Vol 10 (1) ◽  
pp. 45-74 ◽  
Author(s):  
Mojtaba Aghajani ◽  
S. Ali Torabi
Keyword(s):  
Programming Model ◽  
Dynamic Environment ◽  
Sensitivity Analyses ◽  
Mixed Integer ◽  
Critical Parameters ◽  
Content Type ◽  
Procurement Process ◽  
Non Linear Programming ◽  
Supply Policy ◽  
Post Disaster

Purpose The purpose of this paper is to improve the relief procurement process as one of the most important elements of humanitarian logistics. For doing so, a novel two-round decision model is developed to capture the dynamic nature of the relief procurement process by allowing demand updating. The model accounts for the supply priority of items at response phase as well. Design/methodology/approach A mixed procurement/supply policy is developed through a mathematical model, which includes spot market procurement and a novel procurement auction mechanism combining the concepts of multi-attribute and combinatorial reverse auctions. The model is of bi-objective mixed-integer non-linear programming type, which is solved through the weighted augmented e-constraint method. A case study is also provided to illustrate the applicability of the model. Findings This study demonstrates the ability of proposed approach to model post-disaster procurement which considers the dynamic environment of the relief logistics. The sensitivity analyses provide useful managerial insights for decision makers by studying the impacts of critical parameters on the solutions. Originality/value This paper proposes a novel reverse auction framework for relief procurement in the form of a multi-attribute combinatorial auction. Also, to deal with dynamic environment in the post-disaster procurement, a novel two-period programming model with demand updating is proposed. Finally, by considering the priority of relief items and model’s applicability in the setting of relief logistics, post-disaster horizon is divided into three periods and a mixed procurement strategy is developed to determine an appropriate supply policy for each period.

scholarly journals Emergency Vehicle Dispatching and Redistribution in Highway Network Based on Bilevel Programming

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Xiaohong Duan ◽  
Shouxin Song ◽  
Jiandong Zhao
Keyword(s):  
Bilevel Programming ◽  
Programming Model ◽  
Time Windows ◽  
Emergency Vehicle ◽  
Shuffled Frog Leaping Algorithm ◽  
Coverage Area ◽  
Vehicle Dispatching ◽  
Emergency Vehicles ◽  
Shuffled Frog Leaping ◽  
Bilevel Programming Model

Response time is a key factor in the emergency vehicle dispatching problem. Because regional emergency vehicles are limited, vehicle gaps will be created in the rescue station after vehicles are dispatched to several accidents, which affects quick response to the subsequent incidents. To solve this problem, a bilevel programming model for emergency vehicle dispatching and redistribution is established, of which the optimal objectives are the shortest rescue time for current accidents and the shortest time for vehicle redistribution, and the key constraints are emergency vehicle requirements and accident time windows. In the precondition of effective rescue of current accidents, emergency vehicles are redistributed according to the potential risks in the rescue station coverage area. A bilevel shuffled frog leaping algorithm is proposed to solve the bilevel programming model. The dispatching results of examples show that the model conforms to dispatching decision rule and the bilevel shuffled frog leaping algorithm can resolve the bilevel programming model fast and efficiently.

Integrated post-disaster medical assistance team scheduling and relief supply distribution

2018 ◽  
Vol 29 (4) ◽  
pp. 1279-1305 ◽  
Author(s):  
Shengbin Wang ◽  
Feng Liu ◽  
Lian Lian ◽  
Yuan Hong ◽  
Haozhe Chen
Keyword(s):  
Programming Model ◽  
Real Data ◽  
Humanitarian Logistics ◽  
Mixed Integer ◽  
Medical Assistance ◽  
Content Type ◽  
Support Tool ◽  
Numerical Example ◽  
Proposed Model ◽  
Post Disaster

Purpose The purpose of this paper is to solve a post-disaster humanitarian logistics problem in which medical assistance teams are dispatched and the relief supplies are distributed among demand points. Design/methodology/approach A mixed integer-programming model and a two-stage hybrid metaheuristic method are developed to solve the problem. Problem instances of various sizes as well as a numerical example based on the 2016 Kyushu Earthquake in Japan are used to test the proposed model and algorithm. Findings Computational results based on comparisons with the state-of-the-art commercial software show that the proposed approach can quickly find near-optimal solutions, which is highly desirable in emergency situations. Research limitations/implications Real data of the parameters of the model are difficult to obtain. Future collaborations with organizations such as Red Cross and Federal Emergency Management Agency can be extremely helpful in collecting data in humanitarian logistics research. Practical implications The proposed model and algorithm can help governments and non-governmental organizations (NGOs) to effectively and efficiently allocate and coordinate different types of humanitarian relief resources, especially when these resources are limited. Originality/value This paper is among the first ones to consider both medical team scheduling (routing) and relief aid distribution as decision variables in the humanitarian logistics field. The contributions include developing a mathematical model and a heuristic algorithm, illustrating the model and algorithm using a numerical example, and providing a decision support tool for governments and NGOs to manage the relief resources in disasters.

The post-disaster emergency planning problem with facility location and people/resource assignment

Kybernetes ◽  
2019 ◽  
Vol 49 (10) ◽  
pp. 2385-2418
Author(s):  
Jian Wang ◽  
Chenqi Situ ◽  
Mingzhu Yu
Keyword(s):  
Programming Model ◽  
Mathematical Formulation ◽  
Emergency Planning ◽  
Planning Problem ◽  
Distribution Centers ◽  
Content Type ◽  
Medical Centers ◽  
Primary Model ◽  
Post Disaster ◽  
Different Levels

Purpose This paper aims to study a dynamic post-disaster emergency planning (PDEP) problem in an integrated network through the investigation of the selection of shelters, medical centers and distribution centers (DCs), and the allocation of evacuees and injured people. The resource and people assignment in multiple periods are considered. Design/methodology/approach A mathematical formulation is provided for the PDEP problem. The authors decompose the model into two sub-models as follows: the primary model is an integer programming model and the subproblem is a nonlinear programming model with continuous variables. The simulated annealing is used to solve the primary problem, and particle swarm optimization (PSO) mixed with beetle antennae search (BAS) is used to solve the subproblem. Findings The paper finds that BAS can increase the stability of PSO and keep the advantages of PSO’s rapid convergence. By implementing these algorithms on emergency planning after the Wenchuan earthquake that happened in China in 2008, this paper finds that the priority of different levels of injured people is influenced by several factors. Even within the same disaster, the priority of different levels of injured can be inconsistent because of the differences in resource levels. Originality/value The authors integrate the shelters, medical centers and DCs as a system, and simultaneously, consider evacuees and injured people and different resource assignments. The authors divide the injured people into three levels and use survival rate function to simulate the survival conditions of different people. The authors provide an improved PSO algorithm to solve the problem.

scholarly journals Optimization for Service Routes of Pallet Service Center Based on the Pallet Pool Mode

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Kang Zhou ◽  
Shiwei He ◽  
Rui Song
Keyword(s):  
Shortest Path ◽  
Programming Model ◽  
Time Windows ◽  
Method Of Lines ◽  
Chance Constrained Programming ◽  
Service Center ◽  
Chinese Postman Problem ◽  
Routing Problem ◽  
Hybrid Intelligent Algorithm ◽  
Constrained Programming

Service routes optimization (SRO) of pallet service center should meet customers’ demand firstly and then, through the reasonable method of lines organization, realize the shortest path of vehicle driving. The routes optimization of pallet service center is similar to the distribution problems of vehicle routing problem (VRP) and Chinese postman problem (CPP), but it has its own characteristics. Based on the relevant research results, the conditions of determining the number of vehicles, the one way of the route, the constraints of loading, and time windows are fully considered, and a chance constrained programming model with stochastic constraints is constructed taking the shortest path of all vehicles for a delivering (recycling) operation as an objective. For the characteristics of the model, a hybrid intelligent algorithm including stochastic simulation, neural network, and immune clonal algorithm is designed to solve the model. Finally, the validity and rationality of the optimization model and algorithm are verified by the case.

scholarly journals Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 598 ◽  
Author(s):  
Zhiping Zuo ◽  
Yanhui Li ◽  
Jing Fu ◽  
Jianlin Wu
Keyword(s):  
Simulated Annealing ◽  
Tabu Search ◽  
Simulated Annealing Algorithm ◽  
Programming Model ◽  
Search Algorithm ◽  
Time Windows ◽  
Neighborhood Search ◽  
Tabu Search Algorithm ◽  
Service Personnel ◽  
The Stability

In situations where an organization has limited human resources and a lack of multi-skilled employees, organizations pay more and more attention to cost control and personnel arrangements. Based on the consideration of the service personnel scheduling as well as the routing arrangement, service personnel of different skills were divided into different types according to their multiple skills. A mathematical programming model was developed to reduce the actual cost of organization. Then, a hybrid meta heuristic that combines a tabu search algorithm with a simulated annealing was designed to solve the problem. This meta heuristic employs several neighborhood search operators and integrates the advantages of both the tabu search algorithm and the simulated annealing algorithm. Finally, the stability and validity of the algorithm were validated by the tests of several kinds of examples.

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