scholarly journals A Mathematical Model for Scheduling and Assignment of Customers in Hospital Waste Collection Routes

2021 ◽  
Vol 11 (22) ◽  
pp. 10557
Author(s):  
Rodrigo Linfati ◽  
Gustavo Gatica ◽  
John Willmer Escobar
Keyword(s):  
Mathematical Model ◽  
Ad Hoc ◽  
Programming Model ◽  
Healthcare Providers ◽  
Geographical Location ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Waste Collection ◽  
Hospital Waste ◽  
Number Of Customers

The collection, transport, and final disposal of hospital waste may cause contamination and disease if improperly handled. Therefore, such residues are hazardous to the health of waste collectors. These wastes are generated by public agencies, such as hospitals, family health centers, dialysis centers, and private healthcare providers. In this study, a mixed-integer linear programming model is proposed for monthly customer scheduling and route assignment. The proposed approach was fulfilled according to customers’ collection frequency, truck capacity, and customer geographical location. The proposed mathematical model successfully balanced the number of customers and the workload during each day. The effectiveness of the proposed model was tested on data obtained from a waste collection company. The model has been implemented in AMPL language, and the performance of commercial solvers, GUROBI and CPLEX, to obtain an optimal solution were tested. The results show the efficiency of the proposed approach to balance the workload concerning previous scheduling is done ad hoc at the company. The use of the formulated model provides an automatic procedure that was previously performed manually. The methodology can be adapted to other companies with similar requirements.

scholarly journals On the Selective Vehicle Routing Problem

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 771 ◽  
Author(s):  
Cosmin Sabo ◽  
Petrică C. Pop ◽  
Andrei Horvat-Marc
Keyword(s):  
Mathematical Model ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Mixed Integer ◽  
The Novel ◽  
Routing Problem ◽  
Proposed Model ◽  
Benchmark Instances ◽  
Number Of Customers ◽  
Optimal Set

The Generalized Vehicle Routing Problem (GVRP) is an extension of the classical Vehicle Routing Problem (VRP), in which we are looking for an optimal set of delivery or collection routes from a given depot to a number of customers divided into predefined, mutually exclusive, and exhaustive clusters, visiting exactly one customer from each cluster and fulfilling the capacity restrictions. This paper deals with a more generic version of the GVRP, introduced recently and called Selective Vehicle Routing Problem (SVRP). This problem generalizes the GVRP in the sense that the customers are divided into clusters, but they may belong to one or more clusters. The aim of this work is to describe a novel mixed integer programming based mathematical model of the SVRP. To validate the consistency of the novel mathematical model, a comparison between the proposed model and the existing models from literature is performed, on the existing benchmark instances for SVRP and on a set of additional benchmark instances used in the case of GVRP and adapted for SVRP. The proposed model showed better results against the existing models.

scholarly journals A Refueling Scheme Optimization Model for the Voyage Charter with Fuel Price Fluctuation and Ship Deployment Consideration

2017 ◽  
Vol 5 (3) ◽  
pp. 267-278 ◽  
Author(s):  
Peng Jia ◽  
Weilun Zhang ◽  
E Wenhao ◽  
Xueshan Sun
Keyword(s):  
Programming Model ◽  
Optimal Solution ◽  
Arma Model ◽  
Maritime Transportation ◽  
Mixed Integer ◽  
Fuel Price ◽  
Shipping Company ◽  
Significant Difference ◽  
Nonlinear Programming Model ◽  
Operation Cycle

Abstract Due to the long operation cycle of maritime transportation and frequent fluctuations of the bunker fuel price, the refueling expenditure of a chartered ship at different time or ports of call make significant difference. From the perspective of shipping company, an optimal set of refueling schemes for a ship fleet operating on different voyage charter routes is an important decision. To address this issue, this paper presents an approach to optimize the refueling scheme and the ship deployment simultaneously with considering the trend of fuel price fluctuations. Firstly, an ARMA model is applied to forecast a time serials of the fuel prices. Then a mixed-integer nonlinear programming model is proposed to maximize total operating profit of the shipping company. Finally, a case study on a charter company with three bulk carriers and three voyage charter routes is conducted. The results show that the optimal solution saves the cost of 437,900 USD compared with the traditional refueling scheme, and verify the rationality and validity of the model.

scholarly journals Optimal Placement of Social Digital Twins in Edge IoT Networks

Sensors ◽  
2020 ◽  
Vol 20 (21) ◽  
pp. 6181
Author(s):  
Olga Chukhno ◽  
Nadezhda Chukhno ◽  
Giuseppe Araniti ◽  
Claudia Campolo ◽  
Antonio Iera ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Social Relationships ◽  
Data Exchange ◽  
Service Discovery ◽  
Programming Model ◽  
Optimal Solution ◽  
Optimal Placement ◽  
Mixed Integer ◽  
Digital Twins ◽  
The Social

In next-generation Internet of Things (IoT) deployments, every object such as a wearable device, a smartphone, a vehicle, and even a sensor or an actuator will be provided with a digital counterpart (twin) with the aim of augmenting the physical object’s capabilities and acting on its behalf when interacting with third parties. Moreover, such objects can be able to interact and autonomously establish social relationships according to the Social Internet of Things (SIoT) paradigm. In such a context, the goal of this work is to provide an optimal solution for the social-aware placement of IoT digital twins (DTs) at the network edge, with the twofold aim of reducing the latency (i) between physical devices and corresponding DTs for efficient data exchange, and (ii) among DTs of friend devices to speed-up the service discovery and chaining procedures across the SIoT network. To this aim, we formulate the problem as a mixed-integer linear programming model taking into account limited computing resources in the edge cloud and social relationships among IoT devices.

Mixed-Integer Programming Model for Fixture Layout Optimization

1999 ◽  
Vol 121 (4) ◽  
pp. 701-708 ◽  
Author(s):  
Q. A. Sayeed ◽  
E. C. De Meter
Keyword(s):  
Integer Programming ◽  
Mixed Integer Programming ◽  
Programming Model ◽  
Optimal Solution ◽  
Geometric Error ◽  
Mixed Integer ◽  
Integer Programming Model ◽  
Mixed Integer Programming Model ◽  
Fea Model ◽  
Candidate Regions

Workpiece deformation during machining is a significant source of machined feature geometric error. This paper presents a linear, mixed integer programming model for determining the optimal locations of locator buttons, supports, and their opposing clamps for minimizing the affect of static workpiece deformation on machined feature geometric error. This model operates on discretized candidate regions as opposed to continuous candidate regions. In addition it utilizes a condensed FEA model of the workpiece in order to minimize model size and computation expense. This model has two advantages over existing nonlinear programming (NLP) formulations. The first is its ability to solve problems in which fixture elements can be placed over multiple regions. The second is that a global optimal solution to this model can be obtained using commercially available software.

Reactive Power Optimization for Distribution Network with Distributed Generators Based on Semi-Definite Programming

2014 ◽  
Vol 1070-1072 ◽  
pp. 809-814
Author(s):  
Lei Dong ◽  
Ai Zhong Tian ◽  
Tian Jiao Pu ◽  
Zheng Fan ◽  
Ting Yu
Keyword(s):  
Mathematical Model ◽  
Reactive Power ◽  
Power Optimization ◽  
Distribution Network ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Reactive Power Optimization ◽  
Global Optimal Solution ◽  
Distributed Generators ◽  
Global Optimal

Reactive power optimization for distribution network with distributed generators is a complicated nonconvex nonlinear mixed integer programming problem. This paper built a mathematical model of reactive power optimization for distribution network and a new method to solve this problem was proposed based on semi-definite programming. The original mathematical model was transformed and relaxed into a convex SDP model, to guarantee the global optimal solution within the polynomial times. Then the model was extended to a mixed integer semi-definite programming model with discrete variables when considering discrete compensation equipment such as capacitor banks. Global optimal solution of this model can be obtained by cutting plane method and branch and bound method. Numerical tests on the modified IEEE 33-bus system show this method is exact and can be solved efficiently.

scholarly journals Location and optimal sizing of photovoltaic sources in an isolated mini-grid

TecnoLógicas ◽  
2019 ◽  
Vol 22 (44) ◽  
pp. 61-80 ◽  
Author(s):  
Juliana Jiménez ◽  
John E. Cardona ◽  
Sandra X. Carvajal
Keyword(s):  
Electric Power ◽  
Power Plants ◽  
Programming Model ◽  
Irradiation Time ◽  
Optimal Solution ◽  
Solar Irradiation ◽  
Mixed Integer ◽  
Voltage Profile ◽  
Power Losses ◽  
Photovoltaic Generators

This article introduces a new mixed integer linear programming model that guarantees the optimal solution to the location and sizing problem of distributed photovoltaic generators in an isolated mini-grid. The solar radiation curves of each node in the mini-grids were considered, and the main objective was to minimize electric power losses in the operation of the system. The model is non-linear in nature because some restrictions are not linear. However, this article proposes the use of linearization techniques to obtain a linear model with a global optimal solution, which can be achieved through commercial solvers; CPLEX in this case. The proposed model was tested in an isolated 14-bus mini-grid, based on real data of topology, demand and generation adapted to a balanced operation. This model shows, as a result, the optimal location of photovoltaic generators and their optimal capacity produced by the maximum active power delivered at the maximum solar irradiation time of the region. It is also evident that the hybrid operation between small hydroelectric power plants and photovoltaic generation improves the network voltage profile and the electric power losses without the use power storage systems.

scholarly journals A Multi-Objective Mathematical Model for Real-Time Employee Assignment in the Service Industry

2021 ◽  
Author(s):  
Gercek Budak ◽  
Xin Chen
Keyword(s):  
Mathematical Model ◽  
Real Time ◽  
Customer Service ◽  
Service Industry ◽  
Programming Model ◽  
Manufacturing Sector ◽  
Mixed Integer ◽  
Multi Objective ◽  
Service Rates ◽  
The Mathematical Model

Abstract The American economy has shifted toward services since the 1980s. The service industry is an important part of economy and is growing quickly in the last three decades. It is more human-capital intensive than the manufacturing sector and there is a shortage of highly-skilled workforce. One solution to this problem is to improve the efficiency through optimization. Because demand in the service industry changes constantly, it is a great challenge to determine the number of employees and their tasks to improve customer service while reducing cost. This article develops a multi-objective mixed-integer linear programming model to dynamically assign employees to different workstations in real time. A case study of the model is solved in less than one second and its pareto optimal solutions determine the number of employees who are assigned to each workstation and the expected customer service times. The mathematical model is robust and provides optimal employee assignment and service rates for workstations in many situations.

Linear Programming Approaches for Multiple-Class Discriminant and Classification Analysis

2010 ◽  
Vol 1 (1) ◽  
pp. 57-80 ◽  
Author(s):  
Minghe Sun
Keyword(s):  
Linear Programming ◽  
Mathematical Programming ◽  
Ad Hoc ◽  
Programming Model ◽  
Mixed Integer ◽  
Support Vector ◽  
Discriminant Functions ◽  
Classification Analysis ◽  
Classification Errors ◽  
Multiple Class

New linear programming approaches are proposed as nonparametric procedures for multiple-class discriminant and classification analysis. A new MSD model minimizing the sum of the classification errors is formulated to construct discriminant functions. This model has desirable properties because it is versatile and is immune to the pathologies of some of the earlier mathematical programming models for two-class classification. It is also purely systematic and algorithmic and no user ad hoc and trial judgment is required. Furthermore, it can be used as the basis to develop other models, such as a multiple-class support vector machine and a mixed integer programming model, for discrimination and classification. A MMD model minimizing the maximum of the classification errors, although with very limited use, is also studied. These models may also be considered as generalizations of mathematical programming formulations for two-class classification. By the same approach, other mathematical programming formulations for two-class classification can be easily generalized to multiple-class formulations. Results on standard as well as randomly generated test datasets show that the MSD model is very effective in generating powerful discriminant functions.

Linear Programming Approaches for Multiple-Class Discriminant and Classification Analysis

2012 ◽  
pp. 291-314 ◽  
Author(s):  
Minghe Sun
Keyword(s):  
Linear Programming ◽  
Mathematical Programming ◽  
Ad Hoc ◽  
Programming Model ◽  
Mixed Integer ◽  
Support Vector ◽  
Discriminant Functions ◽  
Classification Analysis ◽  
Classification Errors ◽  
Multiple Class

New linear programming approaches are proposed as nonparametric procedures for multiple-class discriminant and classification analysis. A new MSD model minimizing the sum of the classification errors is formulated to construct discriminant functions. This model has desirable properties because it is versatile and is immune to the pathologies of some of the earlier mathematical programming models for two-class classification. It is also purely systematic and algorithmic and no user ad hoc and trial judgment is required. Furthermore, it can be used as the basis to develop other models, such as a multiple-class support vector machine and a mixed integer programming model, for discrimination and classification. A MMD model minimizing the maximum of the classification errors, although with very limited use, is also studied. These models may also be considered as generalizations of mathematical programming formulations for two-class classification. By the same approach, other mathematical programming formulations for two-class classification can be easily generalized to multiple-class formulations. Results on standard as well as randomly generated test datasets show that the MSD model is very effective in generating powerful discriminant functions.

An integrated mathematical model of dynamic production and maintenance planning in pumped-storage hydroelectricity

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Farid Asgari ◽  
Fariborz Jolai ◽  
Farzad Movahedisobhani
Keyword(s):  
Mathematical Model ◽  
Exact Solution ◽  
Energy Production ◽  
Programming Model ◽  
Mixed Integer ◽  
Test Problems ◽  
Production Network ◽  
Content Type ◽  
The Difference ◽  
Pumped Storage

Purpose Pumped-storage hydroelectricity (PSH) is considered as an effective method to moderate the difference in demand and supply of electricity. This study aims to understanding of the high capacity of energy production, storage and permanent exploitation has been the prominent feature of pumped-storage hydroelectricity. Design/methodology/approach In this paper, the optimization of energy production and maintenance costs in one of the large Iranian PSH has been discussed. Hence, a mathematical model mixed integer nonlinear programming developed in this area. Minimizing the difference in supply and demand in the energy production network to multiple energies has been exploited to optimal attainment scheme. To evaluate the model, exact solution CPLEX and to solve the proposed programming model, the efficient metaheuristics are utilized by the tuned parameters achieved from the Taguchi approach. Further analysis of the parameters of the problem is conducted to verify the model behavior in various test problems. Findings The results of this paper have shown that the meta-heuristic algorithm has been done in a suitable time, despite the approximation of the optimal answer, and the consequences of research indicate that the model proposed in the studied power plant is applicable. Originality/value In pumped-storage hydroelectricity plants, one of the main challenges in energy production issues is the development of production, maintenance and repair scheduling concepts that improves plant efficiency. To evaluate the mathematical model presented, exact solution CPLEX and to solve the proposed bi-objective mixed-integer linear programming model, set of efficient metaheuristics are used. Therefore, according to the level of optimization performed in the case study, it has caused the improvement of planning by 7%–12% and effective optimization processes.

Sign in / Sign up

Export Citation Format

Share Document