A Decision-Making Tool for the Optimization of Empty Containers' Return in the Liner Shipping: Optimization by Using the Genetic Algorithm

2018 ◽  
Vol 10 (3) ◽  
pp. 39-56
Author(s):  
Naima Belayachi ◽  
Fouzia Amrani ◽  
Karim Bouamrane
Keyword(s):  
Decision Making ◽  
Lower Cost ◽  
Optimal Solution ◽  
Maritime Transportation ◽  
Initial Population ◽  
Transportation Sector ◽  
Empty Containers ◽  
Feasible Solutions ◽  
The Cost ◽  
Decision Making Tool

This article describes how in the maritime transportation sector, containerization represents one of the most remarkable improvements. In fact, the different shipping companies provide great efforts, whose purpose is to reduce the cost of this transport. However, these companies are facing a problem of empty containers, which are not available at some ports of Maritime Transport Network (MTN) to meet the clients' demands. This problem is simply a consequence of the imbalance in the distribution of containers through the MTN due to the set of containers that do not return to the origin port. This work offers a decision-making tool to this problem by proposing an optimal return of empty containers. The proposed application is based on evolutionary heuristics. Its principle is to find an optimal solution from a set of several feasible solutions generated during an initial population in order to enable the search of empty containers at lower cost.

A Decision-Making Tool for the Optimization of Empty Containers' Return in the Liner Shipping: Optimization by Using the Genetic Algorithm

2021 ◽  
pp. 1186-1206
Author(s):  
Naima Belayachi ◽  
Fouzia Amrani ◽  
Karim Bouamrane
Keyword(s):  
Decision Making ◽  
Optimal Solution ◽  
Maritime Transportation ◽  
Initial Population ◽  
Maritime Transport ◽  
Transportation Sector ◽  
Empty Containers ◽  
Feasible Solutions ◽  
The Cost ◽  
Decision Making Tool

This article describes how in the maritime transportation sector, containerization represents one of the most remarkable improvements. In fact, the different shipping companies provide great efforts, whose purpose is to reduce the cost of this transport. However, these companies are facing a problem of empty containers, which are not available at some ports of Maritime Transport Network (MTN) to meet the clients' demands. This problem is simply a consequence of the imbalance in the distribution of containers through the MTN due to the set of containers that do not return to the origin port. This work offers a decision-making tool to this problem by proposing an optimal return of empty containers. The proposed application is based on evolutionary heuristics. Its principle is to find an optimal solution from a set of several feasible solutions generated during an initial population in order to enable the search of empty containers at lower cost.

OPTIMAL FEASIBLE SOLUTIONS TO A ROAD FREIGHT TRANSPORTATION PROBLEM

2020 ◽  
Vol 5 (1) ◽  
pp. 456
Author(s):  
Tolulope Latunde ◽  
Joseph Oluwaseun Richard ◽  
Opeyemi Odunayo Esan ◽  
Damilola Deborah Dare
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Transportation Cost ◽  
North West ◽  
Life Problems ◽  
Basic Feasible Solutions ◽  
Feasible Solutions ◽  
Road Freight Transportation ◽  
The Cost ◽  
Cost Of Transportation

For twenty decades, there is a visible ever forward advancement in the technology of mobility, vehicles and transportation system in general. However, there is no "cure-all" remedy ideal enough to solve all life problems but mathematics has proven that if the problem can be determined, it is most likely solvable. New methods and applications will keep coming to making sure that life problems will be solved faster and easier. This study is to adopt a mathematical transportation problem in the Coca-Cola company aiming to help the logistics department manager of the Asejire and Ikeja plant to decide on how to distribute demand by the customers and at the same time, minimize the cost of transportation. Here, different algorithms are used and compared to generate an optimal solution, namely; North West Corner Method (NWC), Least Cost Method (LCM) and Vogel’s Approximation Method (VAM). The transportation model type in this work is the Linear Programming as the problems are represented in tables and results are compared with the result obtained on Maple 18 software. The study shows various ways in which the initial basic feasible solutions to the problem can be obtained where the best method that saves the highest percentage of transportation cost with for this problem is the NWC. The NWC produces the optimal transportation cost which is 517,040 units.

scholarly journals Converting existing transmission corridors to HVDC is an overlooked option for increasing transmission capacity

2019 ◽  
Vol 116 (28) ◽  
pp. 13879-13884 ◽  
Author(s):  
Liza Reed ◽  
M. Granger Morgan ◽  
Parth Vaishnav ◽  
Daniel Erian Armanios
Keyword(s):  
High Voltage ◽  
Lower Cost ◽  
Optimal Solution ◽  
High Voltage Direct Current ◽  
Right Of Way ◽  
Electricity System ◽  
And Topology ◽  
Cost Strategy ◽  
And Performance ◽  
The Cost

A changing generation mix and growing demand for carbon-free electricity will almost certainly require dramatic changes in the infrastructure and topology of the electricity system. Rather than build new lines, one way to minimize social opposition and regulatory obstacles is to increase the capacity of existing transmission corridors. In addition to upgrading the capacity of high-voltage alternating current (HVAC) lines, we identify a number of situations in which conversion from HVAC to high-voltage direct current (HVDC) is the least-cost strategy to increase the capacity of the corridor. If restricted to the existing right-of-way (ROW), we find DC conversion to be the least-cost, and in some cases the only, option for distances of >200 km or for increases of >50% capacity. Across all configurations analyzed, we assess HVDC conversion to be the lower-cost option at >350 km and >50% capacity increases. While we recognize that capacity expansion through HVDC conversion may be the optimal solution in only some situations, with future improvements in the cost and performance of solid-state power electronics, conversion to HVDC could be attractive in a growing set of circumstances.

scholarly journals INFORMASI AKUNTANSI DIFERENSIAL SEBAGAI ALAT PENGAMBILAN KEPUTUSAN MENYEWA ATAU MEMBELI GEDUNG PADA PT. BPR MILLENIA KANTOR CABANG PAAL DUA

2020 ◽  
Vol 15 (2) ◽  
pp. 211
Author(s):  
Miranda Ellora Kotambunan ◽  
Grace B Nangoi ◽  
Winston Pontoh
Keyword(s):  
Decision Making ◽  
Qualitative Method ◽  
Accounting Information ◽  
Accurate Information ◽  
Alternative Management ◽  
Branch Office ◽  
The Cost ◽  
Decision Making Tool ◽  
Selection Of ◽  
Rent Or Buy

Decision making is the selection of one of the various alternative actions available. In choosing an alternative, management requires precise and accurate information to reduce the possibility of failure of decisions that will be taken by the company. Differential accounting information is very suitable to be used in the selection of several alternatives. The purpose of this study is to determine whether differential accounting information can be used as a decision-making tool so that companies can decide whether to rent or buy a building as a place to operate its branch offices. This research uses descriptive qualitative method by collecting data through interviews and documentation. The results showed that differential accounting information as a decision-making tool can be applied at PT. BPR Millenia Paal Dua Branch Office and the cost to rent a building is lower than buying a building.

scholarly journals Time to explore: Adaptation of exploration under time pressure

2021 ◽  
Author(s):  
Charley M Wu ◽  
Eric Schulz ◽  
Timothy Joseph Pleskac ◽  
Maarten Speekenbrink
Keyword(s):  
Decision Making ◽  
Lower Cost ◽  
Time Pressure ◽  
Cost Benefit ◽  
Decision Time ◽  
Cognitive Constraints ◽  
Evidence Accumulation ◽  
The Cost ◽  
Pressure Changes ◽  
Shed Light

How does time pressure influence exploration and decision-making? We investigate this question using a within-subject design to manipulate decision time (limited vs. unlimited) and use a range of four-armed bandit tasks, designed to independently manipulate uncertainty and expected reward. With limited time, people have less opportunity to perform costly computations, thus shifting the cost-benefit balance of different exploration strategies. Through behavioral, reinforcement learning (RL), reaction time (RT), and evidence accumulation analyses, we show that time pressure changes how people explore and respond to uncertainty. Specifically, participants reduced their uncertainty-directed exploration under time pressure, were less value-directed, and repeated choices more often. Since our analyses relate uncertainty to slower responses and dampened evidence accumulation (i.e., drift rates), this demonstrates a resource-rational shift towards simpler, lower-cost strategies under time pressure. These results shed light on how people adapt their exploration and decision-making strategies to externally imposed cognitive constraints.

scholarly journals Route Planning Based on Genetic Algorithm

2018 ◽  
Vol 10 (2) ◽  
pp. 122 ◽  
Author(s):  
Lin Li ◽  
Yuhua Zhang
Keyword(s):  
Genetic Algorithm ◽  
Fuel Consumption ◽  
Solution Method ◽  
Route Planning ◽  
Optimal Solution ◽  
Initial Population ◽  
Smoothing Algorithm ◽  
Aircraft Fuel ◽  
Consumption Model ◽  
Feasible Solutions

This paper mainly deals with the planning of aviation route and needs to determine the model to find out the shortest path. In this paper, we combine the methods of simulated annealing and genetic algorithm, and obtained the optimal solution method. Firstly, Genetic Algorithm (GA) uses the modified circle algorithm to find some feasible solutions to the approximate initial population, and then transforms them through simulated and crossover operations. This paper also introduces the aircraft fuel consumption model and the cubical smoothing algorithm with five-point approximation to reduce the aircraft fuel consumption and parts loss. The simulation results show that the accuracy of the route planning based on genetic algorithm is higher, while consumes less fuel and takes less sharp turns.

scholarly journals Selecting Optimal Pedestrian Crossing Using Multi-criteria Decision-making

2012 ◽  
Vol 22 (2) ◽  
pp. 105-116 ◽  
Author(s):  
Ljupko Šimunović ◽  
Ivan Grgurević ◽  
Jasmina Pašagić Škrinjar
Keyword(s):  
Decision Making ◽  
Optimal Solution ◽  
Multi Criteria Decision Making ◽  
Rational Analysis ◽  
Safety Level ◽  
Persons With Disabilities ◽  
The Road ◽  
Pedestrian Crossing ◽  
The Cost ◽  
Selection Methodology

Pedestrian crossings are the critical points in the traffic network that need to enable pedestrians to safely cross the road. The safety level depends on the type of pedestrian crossing. The differences between individual types of pedestrian crossings can be noted also in relation to other criteria such as the price, energy, environmental impact, accessibility, etc. Besides, various groups of users assess the quality service differently, even when this refers to the same type of pedestrian crossing. Therefore, optimal solution of a pedestrian crossing has to be selected based on a comprehensive and rational analysis and application of adequate software tools. The selection methodology of an optimal pedestrian crossing is defined using a multi-criteria analysis. In order to view the problem as a whole, four scenarios of evaluating alternatives are foreseen. Four different groups of stakeholders: traffic experts, investors, groups of persons with disabilities and healthy persons (persons not included in the previous three stakeholder groups), who use a pedestrian crossing (according to different age, disability, perception of personal safety, etc.), assessed the importance of the offered criteria. Different groups of users have different preferences in relation to individual groups of criteria, depending on their interests and needs. One group finds the criterion of pedestrian safety the most important one, others think that finances are most important (the cost of construction), some think that accessibility is the most important issue, etc. The solutions obtained in this manner provide insight into the advantages and drawbacks of individual versions. This makes it easier for the decision-makers to select only one variant / alternative from a group of the offered solutions in compliance with the defined criteria and sub-criteria with the aim of defining an optimal pedestrian crossing for a certain spatial and traffic location. KEY WORDS: pedestrian crossing, multi-criteria decision-making, analytical hierarchy process

scholarly journals On Tightly Bounding the Dubins Traveling Salesman's Optimum

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Satyanarayana G. Manyam ◽  
Sivakumar Rathinam
Keyword(s):  
Lower Bound ◽  
Traveling Salesman Problem ◽  
Optimal Solution ◽  
Traveling Salesman ◽  
Motion Constraints ◽  
Euclidean Traveling Salesman Problem ◽  
Problem Instances ◽  
Feasible Solutions ◽  
The Cost ◽  
Dubins Traveling Salesman Problem

The Dubins traveling salesman problem (DTSP) has generated significant interest over the last decade due to its occurrence in several civil and military surveillance applications. This problem requires finding a curvature constrained shortest path for a vehicle visiting a set of target locations. Currently, there is no algorithm that can find an optimal solution to the DTSP. In addition, relaxing the motion constraints and solving the resulting Euclidean traveling salesman problem (ETSP) provide the only lower bound available for the DTSP. However, in many problem instances, the lower bound computed by solving the ETSP is far below the cost of the feasible solutions obtained by some well-known algorithms for the DTSP. This paper addresses this fundamental issue and presents the first systematic procedure for developing tight lower bounds for the DTSP.

scholarly journals The Effect of a Supplier’s Eco-Design on the Economic Benefits of a Supply Chain and Associated Coordination

2021 ◽  
Vol 18 (24) ◽  
pp. 13357
Author(s):  
Junjun Liu ◽  
Yong Geng ◽  
Biao Chen ◽  
Xiqiang Xia
Keyword(s):  
Game Theory ◽  
Decision Making ◽  
Supply Chain ◽  
Optimal Solution ◽  
Economic Benefits ◽  
Theory Model ◽  
Raw Material ◽  
Effort Level ◽  
Decentralized Decision Making ◽  
The Cost

The eco-design of upstream suppliers can reduce the environmental impact from the production process for downstream customers. To analyze the effect of suppliers’ eco-design on the economic benefits of up-downstream supply chain and the mechanisms, this study constructed a master–slave game theory model for a supplier and a manufacturer. Based on this game theory model, this study comparatively analyzes the effects on raw material/part prices, retail product prices, sale volume, revenue, and eco-design effort level under three conditions (no eco-design, decentralized decision-making with eco-design, centralized decision-making with eco-design). And to further analyze the effect of eco-design costs on the optimal solution, this article takes the supply chain of tire production as an example. This analysis could provide suggestions for the suppliers and manufacturers to develop and improve their eco-design. The main results are as follows: the supplier eco-design is beneficial to improving the overall economic benefits for suppliers and manufacturers under certain conditions, and the range in which a supplier is willing to implement eco-design in a decentralized decision-making situation is wider than that in a centralized decision-making situation; when a supplier implements an eco-design, it will transfer part of the cost to the manufacturer by raising the unit raw material/parts prices. Meanwhile, the manufacturer can reduce the production cost when the benefit of eco-design is more than the increased purchasing price, and they can decrease the retail price to expand the sales volume. Hence, consumers will benefit from lower prices. Thus, it is a multi-win situation among the suppliers, manufacturers, and consumers.

scholarly journals Parameter-dependent shift from rational to irrational decisions in mice

2019 ◽  
Author(s):  
Nathan A. Schneider ◽  
Benjamin Ballintyn ◽  
Donald Katz ◽  
John Lisman ◽  
Hyun-Jae Pi
Keyword(s):  
Decision Making ◽  
Optimal Solution ◽  
Sunk Cost ◽  
Optimal Outcomes ◽  
Economic Choice ◽  
Economic Decision Making ◽  
Biological Substrates ◽  
The Cost ◽  
Parameter Dependent ◽  
Economic Choices

AbstractIn the classical view of economic choices, subjects make rational decisions evaluating the costs and benefits of options in order to maximize their overall income. Nonetheless, subjects often fail to reach optimal outcomes. The overt value of an option drives the direction of decisions, but covert factors such as emotion and sunk cost are thought to drive the observed deviations from optimality. Many questions remain to be answered as to 1) which contexts contribute the most to deviation from an optimal solution; and 2) the extent of these effects. In order to tackle these questions, we devised a decision-making task for mice, in which cost and benefit parameters could be independently and flexibly adjusted and for which a tractable optimal solution was known. Comparing mouse behavior with this optimal solution across parameter settings revealed that the factor most strongly contributing to suboptimality was the cost parameter. The quantification of sunk cost, a covert factor implicated in our task design, revealed it as another contributor to suboptimality. In one condition where the large reward option was particularly unattractive and the small reward cost was low, the sunk cost effect and the cost-led suboptimality almost vanished. In this regime and this regime only, mice could be viewed as close to rational. Taken together, our findings support a model whereby parallel neural circuits independently activate and modulate multiple valuation algorithms, and suggest that “rationality” is a task-specific construct even in mice.Significant StatementIrrational factors in economic decision-making often cause significant deviation from optimal outcomes. By devising a flexible economic choice behavior for mice and comparing their behavior with an optimal solution, we investigated overt and covert factors that contributed to suboptimal outcomes and quantified the deviation from optimality. This investigation identified regimes where mice could be viewed as rational or irrational depending upon the parameters in the same task. These findings may provide a platform to investigate biological substrates underlying rational and irrational decision factors.

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