scholarly journals An Optimal Transportation Schedule of Mobile Equipment

2012 ◽  
Vol 10 (5) ◽  
Author(s):  
S. Guillén-Burguete ◽  
H. Sánchez-Larios ◽  
J.G Vázquez-Vázquez
Keyword(s):  
Optimal Solution ◽  
Road Construction ◽  
Transportation Cost ◽  
Convex Polyhedra ◽  
Mixed Integer ◽  
Time Intervals ◽  
Mixed Integer Linear Program ◽  
Arrival Times ◽  
Indefinite Number ◽  
Total Transportation Cost

Motivated by a problem faced by road construction companies, we develop a new model to obtain an optimaltransportation schedule of mobile machines which have to travel to execute tasks. In this problem, each task ischaracterized by the location where it is to be executed, a work-content in terms of machine-time units, and one ormore time intervals within which it can be performed. The machines can be transported from one location to anotherat any time, thus the problem has an indefinite number of variables. However, this indefinite number of variables canbe reduced to a definite one because, as we prove, the problem has an optimal solution in which the arrivals ofmachines occur only at certain time instants. The objective is to minimize the total transportation cost such that all thetasks are executed within their time intervals. The constraints ensuring that the tasks are processed within theirprescribed time intervals are nonlinear; nevertheless, due to the sets of the possible arrival times of the machinesforming bounded convex polyhedra, our problem can be transformed into a mixed integer linear program by the samedevice used in the decomposition principle of Dantzig-Wolfe.

scholarly journals A Synchronous Optimization Model for Multiship Shuttle Tanker Fleet Design and Scheduling Considering Hard Time Window Constraint

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zhenfeng Jiang ◽  
Dongxu Chen ◽  
Zhongzhen Yang
Keyword(s):  
Time Window ◽  
Programming Model ◽  
Transportation Cost ◽  
Exact Algorithm ◽  
Mixed Integer ◽  
Routing Problem ◽  
Hard Time ◽  
Proposed Model ◽  
Total Transportation Cost ◽  
Time Window Constraints

A Synchronous Optimization for Multiship Shuttle Tanker Fleet Design and Scheduling is solved in the context of development of floating production storage and offloading device (FPSO). In this paper, the shuttle tanker fleet scheduling problem is considered as a vehicle routing problem with hard time window constraints. A mixed integer programming model aiming at minimizing total transportation cost is proposed to model this problem. To solve this model, we propose an exact algorithm based on the column generation and perform numerical experiments. The experiment results show that the proposed model and algorithm can effectively solve the problem.

scholarly journals Liner Shipping Schedule Design for Near-Sea Routes Considering Big Customers’ Preferences on Ship Arrival Time

2020 ◽  
Vol 12 (18) ◽  
pp. 7828 ◽  
Author(s):  
Xi Jiang ◽  
Haijun Mao ◽  
Yadong Wang ◽  
Hao Zhang
Keyword(s):  
Time Windows ◽  
Linear Optimization ◽  
Optimal Solution ◽  
Time Preferences ◽  
Mixed Integer ◽  
Shipping Industry ◽  
Fleet Size ◽  
Arrival Times ◽  
Soft Time Windows ◽  
Mixed Integer Linear Optimization

There usually exist a few big customers at ports of near-sea container shipping routes who have preferences on the weekly ship arrival times due to their own production and sale schedules. Therefore, in practice, when designing ship schedules, carriers must consider such customers’ time preferences, regarded as weekly soft-time windows, to improve customer retention, thereby achieving sustainable development during a depression in the shipping industry. In this regard, this study explores how to balance the tradeoff between the ship total operating costs and penalty costs from the violation of the weekly soft-time windows. A mixed-integer nonlinear nonconvex model is proposed and is further transformed into a mixed-integer linear optimization model that can be efficiently solved by extant solvers to provide a global optimal solution. The proposed model is applied to a near-sea service route from China to Southeast Asia. The results demonstrate that the time preferences of big customers affect the total cost, optimal sailing speeds, and optimal ship arrival times. Moreover, the voyage along a near-sea route is generally short, leaving carriers little room for adjusting the fleet size.

scholarly journals Road network optimization using heuristic and linear programming

2010 ◽  
Vol 56 (No. 3) ◽  
pp. 137-145 ◽  
Author(s):  
R. Ghaffariyan M ◽  
K. Stampfer ◽  
J. Sessions ◽  
T. Durston ◽  
CH. Kanzian ◽  
...  
Keyword(s):  
Network Analysis ◽  
Optimal Solution ◽  
Road Construction ◽  
Mixed Integer ◽  
Shortest Path Algorithm ◽  
Road Density ◽  
The Road ◽  
Constant Cost ◽  
The Cost ◽  
Installation Cost

&nbsp;To minimize the cost of logging, it is necessary to optimize the road density. The aim of this study was to determine optimal road spacing (ORS) in Northern Austria. The stepwise regression method was used in modelling. The production rate of tower yarder was 10.4 m<SUP>3</SUP>/PSHo (Productive system hours) and cost of 19.71 €.m<SUP>–3</SUP>. ORS was studied by calculating road construction cost, installation cost and yarding cost per m<SUP>3</SUP> for different road spacing. The minimum total cost occurred at 39.15 €.m<SUP>–3</SUP> and ORS would be 474 m assuming uphill and downhill yarding. The optimal road density and yarding distance are 21.1 m.ha<SUP>–1</SUP> and 90 m, respectively. A sample logging area was used to plan different roads and, using network analysis, the best solution was found based on a modified shortest path algorithm. The network analysis results were very different from the optimal road spacing results that assumed roads and logging corridors could be located anywhere in the planning area at a constant cost. Mixed integer programming was also used to get a real optimal solution.

Integrated forest harvest planning and road-building model with consideration of economies of scale

2020 ◽  
Vol 50 (10) ◽  
pp. 989-1001
Author(s):  
Azadeh Mobtaker ◽  
Julio Montecinos ◽  
Mustapha Ouhimmou ◽  
Mikael Rönnqvist
Keyword(s):  
Economies Of Scale ◽  
Road Construction ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Road Building ◽  
The Road ◽  
Building Model ◽  
Wood Processing ◽  
Proposed Model ◽  
Transportation Plan

We consider the problem of tactical forest management over a 5-year horizon with yearly periods. The main decisions made consider which harvest areas to cut in each period, the flow of timber from an area to each wood-processing mill to satisfy its annual demand, and which roads to build to access a harvest area not connected to the existing road network. The goal is to minimize the total transportation and road-building costs subject to budget limitations. To explore the benefits of economies of scale (EOS) in road construction, we incorporated this notion in the proposed model. Then, the efficiency of the obtained solution is compared with the model without EOS. The proposed model is a mixed-integer linear program, including several timber assortments and multiple periods. We validated the model for a realistic case in the context of the province of Quebec. The results demonstrate that consideration of EOS significantly reduces the total cost by about 5.3%. In the EOS solution, the road segments that are built every year are very concentrated in specific parts of the region, allowing a road-building company to take advantage of EOS. Moreover, this solution provides a much more efficient timber transportation plan.

scholarly journals ORNInA: A decentralized, auction-based multi-agent coordination in ODT systems

2021 ◽  
pp. 1-17
Author(s):  
Alaa Daoud ◽  
Flavien Balbo ◽  
Paolo Gianessi ◽  
Gauthier Picard
Keyword(s):  
Synthetic Data ◽  
Continuous Optimization ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Mixed Integer Linear Program ◽  
Vehicle Communication ◽  
Vehicle To Vehicle ◽  
Multi Agent ◽  
Run Time ◽  
Agent Coordination

On-Demand Transport (ODT) systems have attracted increasing attention in recent years. Traditional centralized dispatching can achieve optimal solutions, but NP-Hard complexity makes it unsuitable for online and dynamic problems. Centralized and decentralized heuristics can achieve fast, feasible solution at run-time with no guarantee on the quality. Starting from a feasible not optimal solution, we present in this paper a new solution model (ORNInA) consisting of two parallel coordination processes. The first one is a decentralized insertion-heuristic based algorithm to build vehicle schedules in order to solve a particular case of the dynamic Dial-A-Ride-Problem (DARP) as an ODT system, in which vehicles communicate via Vehicle-to-vehicle communication (V2V) and make decentralized decisions. The second coordination scheme is a continuous optimization process namely Pull-demand protocol, based on combinatorial auctions, in order to improve the quality of the global solution achieved by decentralized decision at run-time by exchanging resources between vehicles (k-opt). In its simplest implementation, k is set to 1 so that vehicles can exchange only one resource at a time. We evaluate and analyze the promising results of our contributed techniques on synthetic data for taxis operating in Saint-Étienne city, against a classical decentralized greedy approach and a centralized one that uses a classical mixed-integer linear program (MILP) solver.

scholarly journals Comparative Study of Ranking Methods for Fuzzy Transportation

2019 ◽  
pp. 1592-1602
Author(s):  
Sami Kadhem kareem Al thabhawi
Keyword(s):  
Linear Programming ◽  
Comparative Study ◽  
Programming Model ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Basic Solution ◽  
Ranking Methods ◽  
Fuzzy Variables ◽  
Accurate Comparison ◽  
Total Transportation Cost

There are several methods that are used to solve the traditional transportation problems whose units of supply, demand quantities, and cost transportation are known exactly. These methods obtain basic solution, and develop it to the best solution through a series of consecutive calculations to obtain the optimal solution.The steps are more complex with fuzzy variables, so this paper presents the disadvantages of solutions of the traditional ways with existence of variables in the fuzzy form.This paper also presents a comparison between the results that emerged after using different conversion ranking formulas to convert from fuzzy form to crisp form on the same numerical example with a full fuzzy form. The problem has been then converted into a linear programming model, and the BIG-M method to be later used to find the optimal solution that represents the number of units transferred from processing or supply centers to a number of demand centers based on the known cost of transportation.Achieving the goal of the problem is by finding the lowest total transportation cost,while the comparison is based on that value. The results are presented in acomprehensive table that organizes data and results in a way that facilitates quickand accurate comparison. An amendment to one of the order formats was suggested,because it has different results compared to other formulas. One of the rankingequations is modified, because it has different results compared to other methods..

scholarly journals Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks

2021 ◽  
Vol 11 (22) ◽  
pp. 10547
Author(s):  
Marios Gatzianas ◽  
Agapi Mesodiakaki ◽  
George Kalfas ◽  
Nikos Pleros ◽  
Francesca Moscatelli ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Energy Efficient ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Network Function Virtualization ◽  
User Association ◽  
Computational Resource ◽  
Mixed Integer Linear Program ◽  
Resource Allocation Algorithm ◽  
Network Function

In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the traditional problems of user association and traffic routing, Virtual Network Function (VNF) placement needs to be jointly considered. To that end, in this paper, we focus on the joint network and computational resource allocation, targeting low network power consumption while satisfying the Service Function Chain (SFC), throughput, and delay requirements. Unlike the State-of-the-Art (SoA), we also take into account the Access Network (AN), while formulating the problem as a general Mixed Integer Linear Program (MILP). Due to the high complexity of the proposed optimal solution, we also propose a low-complexity energy-efficient resource allocation algorithm, which was shown to significantly outperform the SoA, by achieving up to 78% of the optimal energy efficiency with up to 742 times lower complexity. Finally, we describe an Orchestration Framework for the automated orchestration of vertical-driven services in Network Slices and describe how it encompasses the proposed algorithm towards optimized provisioning of heterogeneous computation and network resources across multiple network segments.

scholarly journals A Model-Based Optimisation Approach for Process Synthesis of Olefins from Petroleum with Application to the Malaysian Petrochemical Industry

2019 ◽  
Vol 12 ◽  
pp. 1-15
Author(s):  
Khor Cheng Seong
Keyword(s):  
Practical Knowledge ◽  
Optimal Solution ◽  
Raw Material ◽  
Mixed Integer ◽  
Hydrocarbon Mixture ◽  
Continuous Variables ◽  
Mixed Integer Linear Program ◽  
Actual Case ◽  
Model Based ◽  
Recent Developments

The shale gas revolution has rekindled interest in olefins production due to the abundance of ethane as a raw material resource. However, the main technology still revolves around the cost-intensive distillation operation. Hence this work aims to investigate the economic optimisation of olefins synthesis from petroleum in the light of recent developments. A model-based approach is applied to determine the optimal sequencing of separation and reaction processes for a multi-component hydrocarbon mixture feed to produce mainly ethylene and propylene. a mixed-integer linear program (MILP) is formulated based on a superstructure that captures numerous plausible synthesis alternatives. The model comprises linear mass balance reactor representation and simple sharp distillation based on split fractions for product recovery. Integer binary variablesis used for selecting the task for equipment and continuous variables for representing the flowrate of each task. To expedite converging to an optimal solution of a least total annualised cost configuration, the formulation is appended with logical constraints on the design and structural specifications derived from heuristics based on practical knowledge and experience. The modelling approach on actual case studies based on two such petrochemical facilities operating in Malaysia is implemented. Additionally, the solution analysis is enriched with the investigation on a second- and third-best (suboptimal) configurations obtained through appropriate integer cuts as constraints to the model. The results show good agreement with existing plant configurations, thus substantiating the value and verification of the proposed model-based optimisation approach.

scholarly journals A Novel Enhanced Differential Evolution Algorithm for Outbound Logistics of the Poultry Industry in Thailand

2022 ◽  
Vol 8 (1) ◽  
pp. 15
Author(s):  
Karn Moonsri ◽  
Kanchana Sethanan ◽  
Kongkidakhon Worasan
Keyword(s):  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Optimal Solution ◽  
Transportation Cost ◽  
Mixed Integer ◽  
Computational Time ◽  
Poultry Industry ◽  
Routing Problem ◽  
De Algorithm ◽  
Evolution Algorithm

Outbound logistics is a crucial field of logistics management. This study considers a planning distribution for the poultry industry in Thailand. The goal of the study is to minimize the transportation cost for the multi-depot vehicle-routing problem (MDVRP). A novel enhanced differential evolution algorithm (RI-DE) is developed based on a new re-initialization mutation formula and a local search function. A mixed-integer programming formulation is presented in order to measure the performance of a heuristic with GA, PSO, and DE for small-sized instances. For large-sized instances, RI-DE is compared to the traditional DE algorithm for solving the MDVRP using published benchmark instances. The results demonstrate that RI-DE obtained a near-optimal solution of 99.03% and outperformed the traditional DE algorithm with a 2.53% relative improvement, not only in terms of solution performance, but also in terms of computational time.

scholarly journals An Empirical Study on Multi-objective Transportation Problem in Fuzzy Environment

2018 ◽  
Vol 7 (4.38) ◽  
pp. 748
Author(s):  
Manoranjan Mishra ◽  
Debdulal Panda
Keyword(s):  
Transportation Problem ◽  
Optimal Solution ◽  
Fuzzy Rule ◽  
Transportation Cost ◽  
Transportation System ◽  
Vital Role ◽  
Multi Objective ◽  
Transportation Models ◽  
Total Transportation Cost ◽  
Single Objective

For both in economical and social development of country transportation system plays a vital role. As it is directly involved with financial growth of the country, for that a complete well planned transportation infrastructure is necessary. Most of the transportation models are formulated with minimization of transportation cost as the basic objective. But consideration of transportation system with a single objective is not able to meet the various requirements of transportation industry for which it may not lead to the practical optimal solution. It bounds the decision makers (DMs) to consider several objectives at a time instead of single objective. To handle a multi-objective transportation problem with fixed parameters is a challenging issue; rather it is easy to consider all parameters in terms of linguistic variables. In this paper, a multi criteria multi-objective transportation models is formulated based on fuzzy relations under the fuzzy logic with several objectives like (i) minimization of total transportation cost and (ii) minimization of total transportation time. Another objective, maximization of the transported amount from a source to a destination is determined on the basis of previous two objectives. All the objectives are associated with multiple numbers of criteria like breakable items, shipping distance, service charge, mode of transportation etc. These relations are imprecise in nature and represented in terms of verbal words such as low, medium, high and very high. The fuzzy rule based multi-objective transportation problem is formulated and result is discussed. 

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