Investigating Market Integration and Price Transmission of Different Rice Qualities in Iran

Rice production in most of Asian countries has been increased more rapidly than population and this has been led to increase in supply and proportionately decrease in the real price of rice in world and domestic markets. Furthermore, together with growth in production and national gross income of the country per-capita income has been increased and also demand for rice at national and international level quality has been increased. In this case studying the market conditions of different qualities of rice including marketing margins, causative relations among the prices, market integrations in long term and finally price transferring and market integration in short term is the important consequence that can help policymakers and planners in their decision makings on research, production, distribution and marketing of rice strategic product. So, using the statistics from Jihad Agriculture Organization of Guilan Province in case of the price of rice qualities (items) including Sadri momtaz (S1), Sadri darge yek (S2), Sadri mamooli (S3) and Khazar (K1) during 1999-2009 market conditions of different qualities of rice was studied. Results show that impulses in wholesale prices in Khazar rice rapidly influence on-farm prices, however, in case of other rice qualities the rate and speed of this influence is low. But in wholesale-retail market for Sadri quality rice impulses influence strongly in wholesale price and this shows intense integration of these two rice markets in Iran. It is suggested that according to the different quality of rice verities, support policy design and decision making process assigned separatel

Investigating Market Integration and Price Transmission of Different Rice Qualities in Iran

Rice production in most of Asian countries has been increased more rapidly than population and this has been led to increase in supply and proportionately decrease in the real price of rice in world and domestic markets. Furthermore, together with growth in production and national gross income of the country per-capita income has been increased and also demand for rice at national and international level quality has been increased. In this case studying the market conditions of different qualities of rice including marketing margins, causative relations among the prices, market integrations in long term and finally price transferring and market integration in short term is the important consequence that can help policymakers and planners in their decision makings on research, production, distribution and marketing of rice strategic product. So, using the statistics from Jihad Agriculture Organization of Guilan Province in case of the price of rice qualities (items) including Sadri momtaz (S1), Sadri darge yek (S2), Sadri mamooli (S3) and Khazar (K1) during 1999-2009 market conditions of different qualities of rice was studied. Results show that impulses in wholesale prices in Khazar rice rapidly influence on-farm prices, however, in case of other rice qualities the rate and speed of this influence is low. But in wholesale-retail market for Sadri quality rice impulses influence strongly in wholesale price and this shows intense integration of these two rice markets in Iran. It is suggested that according to the different quality of rice verities, support policy design and decision making process assigned separately

A Self-Adaptive Evolutionary Algorithm for the Berth Scheduling Problem: Towards Efficient Parameter Control

Since ancient times, maritime transportation has played a very important role for the global trade and economy of many countries. The volumes of all major types of cargo, which are transported by vessels, has substantially increased in recent years. Considering a rapid growth of waterborne trade, marine container terminal operators should focus on upgrading the existing terminal infrastructure and improving operations planning. This study aims to assist marine container terminal operators with improving the seaside operations and primarily focuses on the berth scheduling problem. The problem is formulated as a mixed integer linear programming model, minimizing the total weighted vessel turnaround time and the total weighted vessel late departures. A self-adaptive Evolutionary Algorithm is proposed to solve the problem, where the crossover and mutation probabilities are encoded in the chromosomes. Numerical experiments are conducted to evaluate performance of the developed solution algorithm against the alternative Evolutionary Algorithms, which rely on the deterministic parameter control, adaptive parameter control, and parameter tuning strategies, respectively. Results indicate that all the considered solution algorithms demonstrate a relatively low variability in terms of the objective function values at termination from one replication to another and can maintain the adequate population diversity. However, application of the self-adaptive parameter control strategy substantially improves the objective function values at termination without a significant impact on the computational time

A Vessel Schedule Recovery Problem at the Liner Shipping Route with Emission Control Areas

Liner shipping is a vital component of the world trade. Liner shipping companies usually operate fixed routes and announce their schedules. However, disruptions in sea and/or at ports affect the planned vessel schedules. Moreover, some liner shipping routes pass through the areas, designated by the International Maritime Organization (IMO) as emission control areas (ECAs). IMO imposes restrictions on the type of fuel that can be used by vessels within ECAs. The vessel schedule recovery problem becomes more complex when disruptions occur at such liner shipping routes, as liner shipping companies must comply with the IMO regulations. This study presents a novel mixed-integer nonlinear mathematical model for the green vessel schedule recovery problem, which considers two recovery strategies, including vessel sailing speed adjustment and port skipping. The objective aims to minimize the total profit loss, endured by a given liner shipping company due to disruptions in the planned operations. The nonlinear model is linearized and solved using CPLEX. A number of computational experiments are conducted for the liner shipping route, passing through ECAs. Important managerial insights reveal that the proposed methodology can assist liner shipping companies with efficient vessel schedule recovery, minimize the monetary losses due to disruptions in vessel schedules, and improve energy efficiency as well as environmental sustainability

A Comprehensive Assessment of the Existing Accident and Hazard Prediction Models for the Highway-Rail Grade Crossings in the State of Florida

Accidents at highway-rail grade crossings can cause fatalities and injuries, as well as significant property damages. In order to prevent accidents, certain upgrades need to be made at highway-rail grade crossings. However, due to limited monetary resources, only the most hazardous highway-rail grade crossings should receive a priority for upgrading. Hence, accident/hazard prediction models are required to identify the most hazardous highway-rail grade crossings for safety improvement projects. This study selects and evaluates the accident and hazard prediction models found in the highway-rail grade crossing safety literature to rank the highway-rail grade crossings in the State of Florida. Three approaches are undertaken to evaluate the candidate accident and hazard prediction models, including the chi-square statistic, grouping of crossings based on the actual accident data, and Spearman rank correlation coefficient. The analysis was conducted for the 589 highway-rail grade crossings located in the State of Florida using the data available through the highway-rail grade crossing inventory database maintained by the Federal Railroad Administration. As a result of the performed analysis, a new hazard prediction model, named as the Florida Priority Index Formula, is recommended to rank/prioritize the highway-rail grade crossings in the State of Florida. The Florida Priority Index Formula provides a more accurate ranking of highway-rail grade crossings as compared to the alternative methods. The Florida Priority Index Formula assesses the potential hazard of a given highway-rail grade crossing based on the average daily traffic volume, average daily train volume, train speed, existing traffic control devices, accident history, and crossing upgrade records

Multiobjective Optimization Model for Emergency Evacuation Planning in Geographical Locations with Vulnerable Population Groups

A large-scale emergency evacuation due to an approaching natural disaster requires local and state administrations to make important decisions regarding evacuation routes, emergency shelters, and evacuation time periods, among other things. Considering a conflicting nature of certain emergency evacuation planning decisions, this study introduces a multiobjective optimization model for emergency evacuation planning that aims to minimize a set of critical performance indicators, including the total evacuation time, mental demand, physical demand, temporal demand, effort, and frustration endured by the individuals evacuating from a given metropolitan area anticipating a natural disaster. The major driver characteristics, evacuation route characteristics, driving conditions, and traffic characteristics that affect the driving performance of individuals, including vulnerable population groups, are incorporated in the proposed mathematical model. In order to solve the developed mathematical model and analyze the trade-offs among the conflicting objectives, this study presents four multiobjective heuristic algorithms. The computational experiments were conducted using real-world data and showcase the efficiency of the proposed methodology. The developed multiobjective methodology is expected to improve the safety of evacuees at the natural disaster preparedness stage and ensure timely evacuation from areas expecting significant natural disaster impacts

Exact and heuristic solution algorithms for efficient emergency evacuation in areas with vulnerable populations

Proper emergency evacuation planning is a key to ensure safety and efficiency of transportation networks in the event of approaching natural hazards. A sound evacuation plan can save human lives and avoid congestion. In order to develop effective emergency evacuation plans, this study presents a mixed-integer programming model that assigns individuals, including vulnerable population groups, to emergency shelters through evacuation routes during the available time periods. The objective of the mathematical model is to minimize the total travel time of individuals leaving an evacuation zone. Unlike many emergency evacuation models presented in the literature, the proposed mathematical model directly accounts for the effects of socio-demographic characteristics of evacuees, evacuation route characteristics, driving conditions, and traffic characteristics on the travel time of evacuees. An exact optimization approach and a set of heuristic approaches are applied to yield solutions for the developed model. The numerical experiments are conducted for emergency evacuation of Broward County (Florida, United States). The results show that the exact optimization approach cannot tackle the large-size problem instances. On the other hand, the proposed heuristic algorithms are able to provide good-quality solutions within a reasonable computational time. Therefore, the developed mathematical model and heuristic algorithms can further assist the appropriate agencies with efficient and timely emergency evacuation planning