Optimization of a multi-constraint transport problem using a heuristic approach

A Linear transport problem can be defined as the action of transporting products from "m origins" (or units) to "n destinations" (or customers) at the lowest cost. So the solution to a transportation problem is to organize the transportation in such a way as to minimize its cost. The objective of this paper is to determine the quantity sent from each source (origin) to each destination while minimizing transport costs. Achieving this objective requires a methodology which consists in deploying an algorithm whose purpose is the search for an optimal solution, based on an initial solution. The application is made on a factory producing mechanical parts.

Solving interval-valued transportation problem using a new ranking function for octagonal fuzzy numbers

In this paper, we introduce a new method to solve Interval-Valued Transportation Problem (IVTP) to deal with those problems of transportation wherein the information available is imprecise. First, a newly proposed fuzzification method is used to convert the IVTP to octagonal fuzzy transportation problem and then with the help of ranking function proposed in this paper, the fuzzy transportation problem is converted into crisp transportation problem. Lastly, Initial Basic Feasible Solution (IBFS) of this problem is obtained using Vogel’s Approximation Method and the solution is improved using Modified Distribution (MODI) method. A numerical example with interval data is solved using the proposed algorithm to make comparison of the solution with some other methods. Also, a numerical example with parameters in the form of octagonal fuzzy numbers is illustrated to compare the effectiveness of the proposed ranking technique. The proposed fuzzification and ranking technique can be used in the other fields of decision making dealing with the data in the same form as considered in this paper.

The Casualty Stabilization–Transportation Problem in a Large-Scale Disaster

We address the problem of picking up, stabilizing, and transporting casualties in response to mass-injury disasters. Our proposed methodology establishes the itinerary for collecting, on-site stabilization, and transporting victims considering capacitated vehicles and medical care centers. Unlike previous works, we minimize the time required to achieve on-site stabilization of each victim according to his age and level of severity of the injuries for their subsequent transfer to specialized medical centers. Thus, more critical patients will be the first to be stabilized, maximizing their chances of survival. In our methodology, the victims’ age, the injuries’ severity level, and their deterioration over time are considered critical factors in prioritizing care for each victim. We tested our approach using simulated earthquake scenarios in the city of Iquique, Chile, with multiple injuries. The results show that explicitly considering the on-site stabilization of the vital functions of the prioritized victims as an objective, before their transfer to a specialized medical center, allows treating and stabilizing patients earlier than with traditional objectives.

A Monge Sequence-Based Approach to Characterize the Competitive Newsvendor Problem

Replicating cash flows of multiple agents in game-theoretic settings tends to be a challenging task. In this paper, we consider the competitive newsvendor game where multiple newsvendors choose inventory levels before demand arrival and the unmet demand of each newsvendor spills over to multiple other newsvendors. We show that this spillover behavior and the resulting cash flows of each newsvendor can be replicated within a transportation problem after assigning artificial costs on spillover behavior. This replication provides an opportunity to study structural properties of the problem, as well as determine the equilibrium of the game. This paradigm of using artificial costs within an optimization framework to replicate agents’ cash flows can be used in many other games as well.