Heuristic algorithm for portfolio selection with minimum transaction lots

Portfolio selection problem was first formulated in a paper written by Markowitz, where investment diversification can be translated into computing. Mean-variance model he introduced has been used and developed because of it’s limitations in the larger constraints found in the real world, as well as it’scomputational complexity which found when it used in large-scale portfolio. Quadratic programming model complexity given by Markowitz has been overcome with the development of the algorithm research. Theyintroduce a linear risk function which solve the portfolio selection problem with real constraints, i.e. minimum transaction lots. With the Mixed Integer Linear models, proposed a new heuristic algorithm that starts from the solution of the relaxation problems which allow finding close-to-optimal solutions. This algorithm is built on Mixed Integer Linear Programming (MILP) which formulated using nearest integer search method

An Integer Optimization Model for the Time Windows Periodic Vehicle Routing Problem with Delivery, Fleet, and Driver Scheduling

The vehicle routing problem (VRP) is a well-known combinatorial optimization problem which describes a homogeneous set of vehicles and routes, in which each vehicle starts from a depot and traverses along a route in order to serve a set of customers with known geographical locations. If the delivery routes are constructed for period of time, the VRP is generalized as periodic VRP (PVRP). This paper develops a model for the optimal management of periodic deliveries of meals of a catering company. The PVRP incorporates time windows, deliveries, fleet and driver scheduling in the periodic planning.. The objective is to minimize the sum of the costs of travelling and elapsed time over the planning horizon. We model the problem as a linear mixed integer program and we propose a feasible neighbourhood direct search approach to solve the problem

A Capacitated Heterogeneous Vehicle Routing Problem for Catering Service Delivery with Committed Scheduled Time

The heterogeneous vehicle routing problem (HVRP) is a well-known combinatorial optimization problem which describes a heterogeneous set of vehicles with different capacity, in which each vehicle starts from a central depot and traverses along a route in order to serve a set of customers with known geographical locations. This paper develops a model for the optimal management of service deliveries of meals of a catering company located in Medan City, Indonesia. The HVRP incorporates time windows, deliveries, fleet scheduling in the committed scheduled time planning.. The objective is to minimize the sum of the costs of travelling and elapsed time over the planning horizon. We model the problem as a linear mixed integer program and we propose a feasible neighbourhood direct search approach to solve the problem

An Optimization Model for Cargo Container Loading Plan Problem for Seafood Products

— Recently Indonesian Government is focusing in marine fishery industry to be one of the key component for developing the economic of the country. Seafood products belong to this industry. In order to distribute rapidly the seafood products around Indonesia the fish industries need air express carrier service. These carrier flights are one-stop, from an origin, to the hub, then to destination. Airport operations include those at the origins, at the destinations and at the hub. In this paper we consider logistics supply chain decision problem which arises in marine fisheries industry in Indonesia. The loading planning problem is to deliver seafood products using air carriers. The objective of the model is to minimize the total container operation costs, subject to the related operating constraints. Due to the perishability of the products, if overflow occurred they should be transported by third party. The model is formulated as a mixed integer programs. We develop a neighborhood search approach for solving the model

Integer Optimization Model for a Location-Allocation-Routing in a Distribution Network with Restrictions on Route

In a distribution network, locating a facility such as supplier is important to decide that could impact not only the profitability of an organization but the ability to serve customers in short time. This paper considers the integrated Location-Allocation-Routing problem such that to minimize the overall cost by simultaneously selecting a subset of candidate facilities and constructing a set of delivery routes that satisfy some restrictions. In this paper we impose restrictions on route, i.e., distance and forbidden route. We use integer programming model to describe the problem. A feasible neighbourhood search is proposed to solve the result model

Mixed Integer Programming Model for open Vehicle Routing Problem with Fleet and driver Scheduling Considering Delivery and Pick-Up Simultaneously

Vehicle Routing Problem (VRP) is a key element of many logistic systems which involve routing and scheduling of vehicles from a depot to a set of customers node. This is a combinatorial optimization problem with the objective to find an optimal set of routes used by a fleet of vehicles to serve a set of customers It is required that these vehicles return to the depot after serving customers’ demand. This paper investigates a variant of VRP, in which the vehicles do not need to return to the depot, called open vehicle routing problem (OVRP). The problem incorporates time windows, fleet and driver scheduling, pick-up and delivery in the planning horizon. The goal is to schedule the deliveries according to feasible combinations of delivery days and to determine the scheduling of fleet and driver and routing policies of the vehicles. The objective is to minimize the sum of the costs of all routes over the planning horizon. We model the problem as a linear mixed integer program. We develop a combination of heuristics and exact method for solving the model

Perencanaan Produksi Makanan Laut dengan Pertimbangan Permintaan dan Kapasitas

The sea holds many resources that are very important for life, and one of them is the potential of fisheries, which is a basic human need. Indonesia, as a maritime country whose waters cover 2/3 of its territory, most of its people who live in coastal areas have utilized this condition by conducting fisheries management activities. However, the process still needs technical support to optimize the results. This research will review the production planning process of processed marine products under demand uncertainty. This research will construct a model to minimize production costs by considering demand uncertainty. The model will be computed using Mixed Integer Linear Program (MILP) method to provide the decision of processed products produced and the amount of production