scholarly journals Addressing Cooperation between Mobile Operators in Telecommunication Networks via Optimization: A Lexicographic Approach and Case Study in Colombia

2020 ◽  
Vol 15 (6) ◽  
Author(s):  
Francisco José MacAllister ◽  
Laura Maya ◽  
Jorge A Huertas ◽  
Carlos Lozano-Garzón ◽  
Yezid Donoso
Keyword(s):  
Optimization Model ◽  
Phase 1 ◽  
Linear Optimization ◽  
Telecommunication Networks ◽  
Mixed Integer ◽  
Marginal Costs ◽  
Lexicographic Optimization ◽  
Mixed Integer Linear Optimization ◽  
Two Phases

Cooperation between Telecommunications (Telco) operators has been limited both by regulation and competition in previous years. However, cooperation could not only allow an overall growth in quality of service (QoS) but also may benefit companies with under exploited nodes in their network infrastructure. This way, both fully deployed infrastructure by single Telco companies, as well as smaller companies with increasing service demand but low infrastructure deployment could potentially benefit from cooperation agreements. This article proposes a lexicographic mixed-integer linear optimization model for Telco cooperation composed by two phases: Phase 1 maximizes the number of services connected to the current infrastructure assuming cooperation between operators while Phase 2 minimizes the costs of connecting such services. We built a simple base scenario that allowed us to validate the intuition behind our model. Furthermore, to demonstrate the applicability of our lexicographic optimization model for cooperation between mobile operators, we present a real-world case study in a rural area in Colombia that allowed us to find the marginal costs of additional national roaming connections, as well as marginal profits under the cooperation schema. Our results could help mobile operators to benefit from cooperation and, since the model adapts to the local necessities of the company, cooperation could be restricted to any desired level.

scholarly journals A scenario-based optimization model for planning and redesigning the sale and after-sales services closed-loop supply chain

2020 ◽  
Author(s):  
Nazanin Esmaeili ◽  
Ebrahim Teimoury ◽  
Fahimeh Pourmohammadi
Keyword(s):  
Supply Chain ◽  
Customer Satisfaction ◽  
Optimization Model ◽  
Linear Optimization ◽  
Spare Parts ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Warranty Period ◽  
Linear Optimization Model ◽  
Mixed Integer Linear Optimization

In today's competitive world, the quality of after-sales services plays a significant role in customer satisfaction and customer retention. Some after-sales activities require spare parts and owing to the importance of customer satisfaction, the needed spare parts must be supplied until the end of the warranty period. In this study, a mixed-integer linear optimization model is presented to redesign and plan the sale and after-sales services supply chain that addresses the challenges of supplying spare parts after the production is stopped due to demand reduction. Three different options are considered for supplying spare parts, including production/procurement of extra parts while the product is being produced, remanufacturing, and procurement of parts just in time they are needed. Considering the challenges of supplying spare parts for after-sales services based on the product's life cycle is one contribution of this paper. Also, this paper addresses the uncertainties associated with different parameters through Mulvey's scenario-based optimization approach. Applicability of the model is investigated using a numerical example from the literature. The results indicate that the production/procurement of extra parts and remanufacturing are preferred to the third option. Moreover, remanufacturing is recommended when the remanufacturing cost is less than 23% of the production cost.

scholarly journals Modelling price scenarios for sustainable collective action and farm production: pepper in El Roble settlement, Costa Rica

2015 ◽  
Vol 15 (1) ◽  
pp. 39-59
Author(s):  
F. Sáenz-Segura ◽  
R.A. Schipper ◽  
D. Miranda ◽  
J.M. Chaves
Keyword(s):  
Costa Rica ◽  
Local Development ◽  
Linear Optimization ◽  
Production Costs ◽  
Mixed Integer ◽  
Piper Nigrum ◽  
Fixed Costs ◽  
Marginal Costs ◽  
Mixed Integer Linear Optimization ◽  
High Level

Pepper (Piper nigrum L.) is considered a non-traditional cash crop for enhancing local development in Costa Rica and a suitable activity for small farmers. Trade of pepper has been done by using contractual agreements between producers and processors, which provides at least three functions: insurance, incentives and information. Contracts also require a high level of commitment from contracting parties to keep the equity, efficiency, and sustainability of the trade relationship. The shift of trade conditions from a competitive to a monopsony market encouraged a group of farmers to start an association that aims to bulk and process pepper from members. Breaching contracts by members of the association endanger this effort of sustainable entrepreneurship. This usually happens when temporary market conditions yield higher procurement prices by other competitors. This situation is also worsened by the lack of proper information on production and processing costs between the contracting parties, and then, the disagreement on the procurement price fixation and payment conditions. By using a mixed integer linear optimization model, we aim to identify the ‘best’ price of fresh pepper traded between both parties. We make use of primary information from 12 different farms on production costs and from the association on processing costs. The model incorporates minimum required net margins for all contracting parties, while modelling the net margins of each party, the amount of traded fresh pepper and preferred contract possibilities, given different fresh pepper price scenarios. At lower prices, some of the farmers that supply pepper, do this to just break-even. At higher prices, more is supplied by more farmers. Under monopsony conditions and individual contracts between parties, it is in the interest of the buyer to offer higher fresh pepper prices in order to buy and process more pepper, up to the point that the marginal costs of buying more pepper are equal to the marginal benefits of that extra pepper. This is because the processor has fixed costs, next to variable costs. Higher volumes reduce the average total costs of processing per kg of pepper, and thereby increase profit. When group contracts are possible, thus under bilateral monopoly conditions – farmers acting as ‘one’ seller and the processor as the only buyer – more fresh pepper is supplied at higher prices than under monopsony conditions as more farmers would have higher surpluses. At the same time the processor would have a higher profit than using individual contracts.

Optimal Test Assembly in Practice

2013 ◽  
Vol 221 (3) ◽  
pp. 190-200 ◽  
Author(s):  
Jörg-Tobias Kuhn ◽  
Thomas Kiefer
Keyword(s):  
Particle Physics ◽  
Large Scale ◽  
Block Design ◽  
Linear Optimization ◽  
Mixed Integer ◽  
Optimal Test ◽  
Automated Test Assembly ◽  
Test Assembly ◽  
Block Level ◽  
Mixed Integer Linear Optimization

Several techniques have been developed in recent years to generate optimal large-scale assessments (LSAs) of student achievement. These techniques often represent a blend of procedures from such diverse fields as experimental design, combinatorial optimization, particle physics, or neural networks. However, despite the theoretical advances in the field, there still exists a surprising scarcity of well-documented test designs in which all factors that have guided design decisions are explicitly and clearly communicated. This paper therefore has two goals. First, a brief summary of relevant key terms, as well as experimental designs and automated test assembly routines in LSA, is given. Second, conceptual and methodological steps in designing the assessment of the Austrian educational standards in mathematics are described in detail. The test design was generated using a two-step procedure, starting at the item block level and continuing at the item level. Initially, a partially balanced incomplete item block design was generated using simulated annealing, whereas in a second step, items were assigned to the item blocks using mixed-integer linear optimization in combination with a shadow-test approach.

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